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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29995?offset=230</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment</guid>
	<pubDate>Mon, 02 Jun 2014 18:03:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment</link>
	<title><![CDATA[Next generation sequencing in R or bioconductor environment]]></title>
	<description><![CDATA[<p>There are many R software and bioconductor packages for NGS data analysis, some of them are as follows</p><h3><a name="TOC-Biostrings" id="TOC-Biostrings"></a>Biostrings</h3><p>The Biostrings package from Bioconductor provides an advanced environment for efficient sequence management and analysis in R. It contains many speed and memory effective string containers, string matching algorithms, and other utilities, for fast manipulation of large sets of biological sequences. The objects and functions provided by Biostrings form the basis for many other sequence analysis packages. <a href="http://bioconductor.org/packages/release/bioc/html/Biostrings.html">Documentation</a></p><div><div style="text-align: left;"><div style="color: #000000;"><h4><a name="TOC-IRanges-Overview" id="TOC-IRanges-Overview"></a>IRanges Overview</h4><p>IRanges provides the low-level infrastructure and containers for handling sets of integer ranges within Bioconductor's BioC-Seq domain. Its classes and methods provide support for many more high-level packages like GenomicRanges, ShortRead, Rsamtools, etc. <a href="http://bioconductor.org/packages/release/bioc/html/IRanges.html">Documentation</a></p><div style="text-align: right;"><div style="text-align: left;"><h4><a name="TOC-GenomicRanges-Overview" id="TOC-GenomicRanges-Overview"></a>GenomicRanges Overview</h4><p>The <em>GenomicRanges</em> package serves as the foundation for representing genomic locations within the Bioconductor project. It is built upon the <em>IRanges</em> infrastructure and defines three major data containers - <em>GRanges, GRangesList</em> and <em>GappedAlignments</em> - which are supporting other important BioC-Seq packages including <em>ShortRead, Rsamtools, rtracklayer, GenomicFeatures</em> and <em>BSgenome</em>.&nbsp; Compared to the IRanges container, the GRanges/<em>GRangesList</em> classes are more flexible and extensible to store additional information about sequence ranges, such as chromosome identifiers (sequence space), strand information and annotation data. <a href="http://bioconductor.org/packages/release/bioc/html/GenomicRanges.html">Documentation</a></p></div></div></div></div><h3><a name="TOC-Motif-Discovery" id="TOC-Motif-Discovery"></a>Motif Discovery</h3><h4><a name="TOC-cosmo" id="TOC-cosmo"></a>cosmo</h4><p>The cosmo package allows to search a set of unaligned DNA sequences for a shared motif that may function as transcription factor binding site. The algorithm extends the popular motif discovery tool MEME (Bailey and Elkan, 1995) in that it allows the search to be supervised by specifying a set of constraints that the motif to be discovered must satisfy. <a href="http://bioconductor.org/packages/release/bioc/html/cosmo.html">Documentation</a></p></div><div>
<p><span></span><span></span></p>
<div style="color: #0000ff;"><h4><a name="TOC-BCRANK" id="TOC-BCRANK"></a>BCRANK</h4><p>BCRANK is a method that takes a ranked list of genomic regions as input and outputs short DNA sequences that are overrepresented in some part of the list. The algorithm was developed for detecting transcription factor (TF) binding sites in a large number of enriched regions from high-throughput ChIP-chip or ChIP-seq experiments, but it can be applied to any ranked list of DNA sequences. Documentation</p>
<p><a href="http://bioconductor.org/packages/release/bioc/html/BCRANK.html"></a></p>
<p>rGADEM: <a href="http://bioconductor.org/packages/devel/bioc/html/rGADEM.html">Documentation</a></p><p>MotIV: <a href="http://bioconductor.org/packages/devel/bioc/html/MotIV.html">Documentation</a></p></div><h3><a name="TOC-ShortRead" id="TOC-ShortRead"></a>ShortRead</h3><p>The ShortRead package provides input, quality control, filtering, parsing, and manipulation functionality for short read sequences produced by high throughput sequencing technologies. While support is provided for many sequencing technologies, this package is primairly focused on Solexa/Illumina reads. <a href="http://bioconductor.org/packages/release/bioc/html/ShortRead.html">Documentation</a></p><h3><a name="TOC-Rsamtools" id="TOC-Rsamtools"></a>Rsamtools</h3><p>Rsamtools provides functions for parsing and inspecting samtools BAM formatted binary alignment data. SAM/BAM is quickly becoming a universal standard alignment format, and is now supported by a wide variety of alignment tools. <a href="http://bioconductor.org/help/bioc-views/2.7/bioc/html/Rsamtools.html">Documentation</a></p>
<p><a href="http://samtools.sourceforge.net/">Samtools Website</a><br /> <a href="http://bio-bwa.sourceforge.net/">BWA (Burrows-Wheeler Alignment) Website</a><br /><span style="color: #0000ff;"></span></p>
<div style="color: #000000;">&nbsp;</div></div><div>
<p><span style="color: #000000;">Additional tools for SNP analysis:&nbsp;</span></p>
<p><a href="http://bioconductor.org/help/bioc-views/release/bioc/html/snpMatrix.html">snpMatrix</a></p><h3><a name="TOC-BSgenome" id="TOC-BSgenome"></a>BSgenome</h3><p>BSgenome provides an object oriented infrastructure for interacting with a Biostring based genome sequence. BSgenome packages exist for many common genomes, and can be created to represent custom genomes. See the "How to forge a BSgenome data package" Vignette for instructions to create a new BSgenome package if a prebuilt package does not exist for your organism. <a href="http://bioconductor.org/packages/release/bioc/html/BSgenome.html">Documentation</a></p><h3><a name="TOC-rtracklayer" id="TOC-rtracklayer"></a>rtracklayer</h3><p>rtracklayer provides an interface for exporting annotation feature data to various genome browsers and file formats (such as GFF). See the Small RNA Profiling exercise for an example of using rtracklayer to visualize alignment coverage. <a href="http://bioconductor.org/packages/release/bioc/html/rtracklayer.html">Documentation</a></p><h3><a name="TOC-biomaRt" id="TOC-biomaRt"></a>biomaRt</h3><p>The biomaRt package, provides an interface to a growing collection of databases implementing the BioMart software suite (http:// www.biomart.org). The package enables online retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas. This data is retrieved automatically via the Internet, so it's recommended that you cache the data locally, or check versions if your code will be adversely affected by updates to these data. <a href="http://bioconductor.org/packages/release/bioc/html/biomaRt.html">Documentation</a></p><h3><a name="TOC-ChIP-Seq-Analysis-Packages" id="TOC-ChIP-Seq-Analysis-Packages"></a>ChIP-Seq Analysis Packages</h3><p>Bioconductor provides various packages for analyzing and visualizing ChIP-Seq data. Only a small selection of these packages is introduced here. Additional useful introductions to this topic are: <a href="http://www.bioconductor.org/workshops/2009/SeattleJan09/ChIP-seq/">BioC ChIP-seq Case Study</a> and BioC <a href="http://www.bioconductor.org/help/course-materials/2009/SeattleNov09/ChIP-seq/">ChIP-Seq</a>.</p><h4><a name="TOC-chipseq" id="TOC-chipseq"></a>chipseq</h4><p>The chipseq package combines a variety of HT-Seq packages to a pipeline for ChIP-Seq data analysis. <a href="http://bioconductor.org/packages/release/bioc/html/chipseq.html">Documentation</a></p><h4><a name="TOC-BayesPeak" id="TOC-BayesPeak"></a>BayesPeak</h4><p>BayesPeak is a peak calling package for identifying DNA binding sites of proteins in ChIP-Seq experiments. Its algorithm uses hidden Markov models (HMM) and Bayesian statistical methods. The following sample code introduces the identification of peaks with the BayesPeak package as well as the incorporation of read coverage information obtained by the chipseq package. <a href="http://bioconductor.org/packages/release/bioc/html/BayesPeak.html">Documentation</a> [ <a href="http://www.biomedcentral.com/1471-2105/10/299">Publication</a> ]</p><h4><a name="TOC-PICS" id="TOC-PICS"></a>PICS</h4><p>The PICS package applies probabilistic inference to aligned-read ChIP-Seq data in order to identify regions bound by transcription factors. PICS identifies enriched regions by modeling local concentrations of directional reads, and uses DNA fragment length prior information to discriminate closely adjacent binding events via a Bayesian hierarchical t-mixture model. The following sample code uses the test data set from the above BayesPeak package in order to compare the results from both methods by identifying their consensus peak set. <a href="http://www.bioconductor.org/packages/release/bioc/html/PICS.html">Documentation</a> [ <a href="http://www.hubmed.org/display.cgi?uids=20528864">Publication</a> ]</p><h4><a name="TOC-ChIPpeakAnno" id="TOC-ChIPpeakAnno"></a>ChIPpeakAnno</h4><p>The ChIPpeakAnno package provides. batch annotation of the peaks identified from either ChIP-seq or ChIP-chip experiments. It includes functions to retrieve the sequences around peaks, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. The package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages. <a href="http://bioconductor.org/packages/release/bioc/html/ChIPpeakAnno.html">Documentation</a></p><h4><a name="TOC-Additional-ChIP-Seq-Packages" id="TOC-Additional-ChIP-Seq-Packages"></a>Additional ChIP-Seq Packages</h4><p>DiffBind: <a href="http://www.bioconductor.org/packages/release/bioc/html/DiffBind.html">Documentation</a></p><p>MOSAICS: <a href="http://bioconductor.org/packages/devel/bioc/html/mosaics.html">Documentation</a></p><p>iSeq: <a href="http://bioconductor.org/packages/release/bioc/html/iSeq.html">Documentation</a></p><p>ChIPseqR: <a href="http://bioconductor.org/packages/release/bioc/html/ChIPseqR.html">Documentation</a></p><p>ChiPsim: <a href="http://bioconductor.org/packages/release/bioc/html/ChIPsim.html">Documentation</a></p><p>CSAR: <a href="http://www.bioconductor.org/packages/devel/bioc/html/CSAR.html">Documentation</a></p><p>ChIP-Seq Pipeline: <a href="http://www.bioconductor.org/packages/release/bioc/html/PICS.html">PICS</a>, rGADEM and MotIV (<a href="http://www.rglab.org/pics-and-bioconductor/">developer web site</a>)</p><p>SPP: <a href="http://compbio.med.harvard.edu/Supplements/ChIP-seq/">ChIP-seq processing pipeline</a></p><p><a href="http://compbio.med.harvard.edu/Supplements/ChIP-seq/tutorial.html">SPP Tutorial</a></p><p><a href="http://liulab.dfci.harvard.edu/MACS/index.html">MACS</a></p><p><a href="http://gmdd.shgmo.org/Computational-Biology/ChIP-Seq/download/SIPeS">SIPeS</a></p><h3><a name="TOC-RNA-Seq-Analysis" id="TOC-RNA-Seq-Analysis"></a>RNA-Seq Analysis</h3><h4><a name="TOC-Counting-Reads-that-Overlap-with-Annotation-Ranges-" id="TOC-Counting-Reads-that-Overlap-with-Annotation-Ranges-"></a>Counting Reads that Overlap with Annotation Ranges&nbsp;</h4><p>The GenomicRanges package provides support for importing into R short read alignment data in BAM format (via Rsamtools) and associating them with genomic feature ranges, such as exons or genes. This way one can quantify the number of reads aligning to annotated genomic regions. The package defines general purpose containers for storing genomic intervals as well as more specialized containers for storing alignments against a reference genome. The two main functions for read counting provided by this infrastructure are <span>countOverlaps <span style="color: #000000;"><span>and</span></span> summarizeOverlaps</span>. For their proper usage, it is important to read the corresponding <a href="http://www.bioconductor.org/packages/devel/bioc/vignettes/GenomicRanges/inst/doc/summarizeOverlaps.pdf">PDF manual</a>. <a href="http://bioconductor.org/packages/release/bioc/html/GenomicRanges.html">Documentation</a></p><h4><a name="TOC-Differential-Gene-Expression-Analysis-with-DESeq" id="TOC-Differential-Gene-Expression-Analysis-with-DESeq"></a>Differential Gene Expression Analysis with DESeq</h4><p>The DESeq package contains functions to call differentially expressed genes (DEGs) in count tables based on a model using the negative binomial distribution. It expects as input a data frame with the raw read counts per region/gene of interest (rows) for each test sample (columns).&nbsp; Such a count table can be imported into R or generated from BAM alignment files using the <span>countOverlaps</span> function as introduced above. <a href="http://www.bioconductor.org/packages/release/bioc/html/DESeq.html">Documentation</a></p><h4><a name="TOC-Differential-Gene-Expression-Analysis-with-edgeR" id="TOC-Differential-Gene-Expression-Analysis-with-edgeR"></a>Differential Gene Expression Analysis with edgeR</h4><p>The edgeR package uses empirical Bayes estimation and exact tests based on the negative binomial distribution to call differentially expressed genes (DEGs) in count data.&nbsp;</p>
<p><a href="http://www.bioconductor.org/packages/release/bioc/html/edgeR.html">Documentation</a></p>
<p><span style="color: #000000;">A variety of additional R packages are available for normalizing RNA-Seq read count data and identifying differentially expressed genes (DEG): <br /> </span></p><p><a href="http://bioconductor.org/packages/devel/bioc/html/easyRNASeq.html">easyRNASeq</a> (simplifies read counting per genome feature)</p><p><a href="http://www.bioconductor.org/packages/release/bioc/html/DEXSeq.html">DEXSeq</a> (Inference of differential exon usage);&nbsp;<a href="http://www.bioconductor.org/packages/release/data/experiment/html/parathyroidSE.html">parathyroidSE</a> explains how to generate exon read counts in R</p><p><a href="http://bioconductor.org/packages/release/bioc/html/DEGseq.html">DEGseq</a></p><p><a href="http://www.bioconductor.org/packages/release/bioc/html/baySeq.html">baySeq</a> (also see: <a href="http://www.bioconductor.org/packages/release/bioc/html/segmentSeq.html">segmentSeq</a>)</p><p><a href="http://bioconductor.org/packages/release/bioc/html/Genominator.html">Genominator</a> (<a href="http://www.hubmed.org/display.cgi?uids=20167110">Bullard et al. 2010</a>)</p><div style="text-align: right;"><div style="text-align: left;"><h4><a name="TOC-Detection-of-Alternative-Splice-Junctions" id="TOC-Detection-of-Alternative-Splice-Junctions"></a>Detection of Alternative Splice Junctions</h4>
<p><span style="color: #000000;">Another utility of RNA-Seq experiments is the analysis of splice junctions. The following software suggestions provide this utility:</span></p>
<p><a href="http://woldlab.caltech.edu/rnaseq/">ERANGE<br /> </a><a href="http://tophat.cbcb.umd.edu/">TopHat</a></p><p><a href="http://biogibbs.stanford.edu/%7Ekinfai/SpliceMap/">SpliceMap</a></p><p><a href="http://solidsoftwaretools.com/gf/project/splitseek/">SplitSeek</a></p><h3><a name="TOC-DNA-Methylation-Data-Analysis" id="TOC-DNA-Methylation-Data-Analysis"></a>DNA-Methylation Data Analysis</h3><div><ul>
<li><span style="font-size: 10pt;"><a href="http://www.bioconductor.org/help/course-materials/2012/BiocEurope2012/mattia_pelizzola_methylPipe.pdf">methylPipe</a></span></li>
<li><span style="font-size: 10pt;"><a href="http://www.bioconductor.org/packages/devel/bioc/html/bsseq.html">bsseq</a></span></li>
<li><a href="http://www.bioconductor.org/packages/devel/bioc/html/BiSeq.html">BiSeq</a></li>
<li>Much more under <a href="http://www.bioconductor.org/packages/devel/BiocViews.html#___DNAMethylation">BiocViews</a></li>
</ul></div></div></div><h3><a name="TOC-HT-Seq-Data-Visualization" id="TOC-HT-Seq-Data-Visualization"></a>HT-Seq Data Visualization</h3>
<p><a href="http://www.bioconductor.org/packages/release/bioc/html/ggbio.html">ggbio</a>: ggplot2 extension for genomics data (<a href="http://tengfei.github.com/ggbio/">online manual</a>) <a href="http://www.bioconductor.org/packages/devel/bioc/html/Gviz.html">Gviz</a>:&nbsp;Plotting data and annotation information along genomic coordinates <a href="http://bioconductor.org/packages/release/bioc/html/HilbertVis.html">HilbertVis</a>: Hilbert genome plots</p>
<p><a href="http://bioconductor.org/packages/release/bioc/html/GenomeGraphs.html">GenomeGraphs</a>: Plotting genomic information from Ensembl</p><p><a href="http://www.hubmed.org/display.cgi?uids=18507856">TileQC</a>: Flow Cell Quality Visualization</p><p><a href="http://bioconductor.org/packages/release/bioc/html/rtracklayer.html">rtracklayer</a>: R interface to genome browsers</p><p><a href="http://genoplotr.r-forge.r-project.org/">genoPlotR</a>: Plotting maps of genes and genomes</p><p><a href="http://bioconductor.org/packages/release/bioc/html/Genominator.html">Genominator</a>: Tools for storing, accessing, analyzing and visualizing genomic data.</p><p>&nbsp;</p><p>To install all packages</p><blockquote><p>source("http://bioconductor.org/biocLite.R")<br />biocLite()<br />biocLite(c("ShortRead", "Biostrings", "IRanges", "BSgenome", "rtracklayer", "biomaRt", "chipseq", "ChIPpeakAnno", "Rsamtools", "BayesPeak", "PICS", "GenomicRanges", "DESeq", "edgeR", "leeBamViews", "GenomicFeatures", "BSgenome.Celegans.UCSC.ce2"))</p></blockquote></div>]]></description>
	<dc:creator>John Parker</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</guid>
	<pubDate>Mon, 06 Oct 2014 12:51:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/17926/orange-bioinformatics-2534</link>
	<title><![CDATA[Orange-Bioinformatics 2.5.34]]></title>
	<description><![CDATA[<p>Orange Bioinformatics extends <a href="http://orange.biolab.si/">Orange</a>, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter is also suitable for non-programmers.</p>
<p>Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.</p><p>Address of the bookmark: <a href="https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34" rel="nofollow">https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18385/biinformamatics-lead-at-google-life-sciences</guid>
  <pubDate>Fri, 17 Oct 2014 02:24:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Biinformamatics Lead at Google Life Sciences]]></title>
  <description><![CDATA[
<p>Google Life Sciences is recruiting a technical lead with experience in bioinformatics and clinical bioinformatics, including for biomarker discovery projects such as the Baseline study.</p>

<p>Responsibilities</p>

<p>Lead teams of scientists in structuring, prototyping, and executing large-scale bioinformatic and other analysis.<br />Develop novel bioinformatics, statistical, data processing, pathway, data mining and other algorithms to identify biological signals and their clinical correlates in broad kinds of individual and population data.<br />Develop novel platform-level analytical tools for sequence-based assays (assembly, annotation, variant calling and interpretation, phasing, genome structure, etc.), expression assays (RNAseq and microarray), proteomics, and metabolomics.<br />Develop statistical models that robustly correlate complex laboratory-derived information with phenotypic and clinical information.<br />Create scientifically rigorous visualizations, communications, and presentations of results.</p>

<p>Reference @ https://www.google.com/about/careers/search#!t=jo&amp;jid=62095001</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/19648/mit-computational-biology-group</guid>
  <pubDate>Thu, 18 Dec 2014 14:47:01 -0600</pubDate>
  <link></link>
  <title><![CDATA[MIT Computational Biology Group]]></title>
  <description><![CDATA[
<p>My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.</p>

<p>We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.</p>

<p>http://compbio.mit.edu/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/22410/nicolas-corradi-lab</guid>
  <pubDate>Tue, 26 May 2015 16:19:02 -0500</pubDate>
  <link></link>
  <title><![CDATA[Nicolas Corradi Lab]]></title>
  <description><![CDATA[
<p>The goal of our research is to better understand the biology of microbial organisms of significant ecological, veterinary and medical importance.<br />To achieve this goal, our team combines the power of next generation DNA sequencing and  bioinformatics with molecular biology and experimental procedures.</p>

<p>Main research topics:<br />- Comparative and Population Genomics of Plant Symbionts<br />- Parasite Genome Evolution<br />- Experimental Evolution of Microbial Symbionts and Parasites<br />- Phylogenomics of Early Branching Fungi</p>

<p>More at http://corradilab.weebly.com/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/24298/staff-scientists-at-national-institute-of-plant-genome-research-new-delhi</guid>
  <pubDate>Fri, 04 Sep 2015 22:06:59 -0500</pubDate>
  <link></link>
  <title><![CDATA[Staff Scientists at National Institute of Plant Genome Research, New Delhi]]></title>
  <description><![CDATA[
<p>National Institute of Plant Genome Research, New Delhi is an Autonomous Research Institution funded by Department of Biotechnology, Ministry of Science &amp; Technology, Govt. of India, to pursue research on various aspects of plant genomics. The Institute is also in the process of establishing a NIPGR Translational Centre at Biotech Science Cluster, NCR, Faridabad. NIPGR invites applications from Indian Citizens for filling up the vacant posts on Direct Recruitment basis, as detailed below. The posts are temporary but likely to continue.</p>

<p>Staff Scientists</p>

<p>Specialization: Applicant should have a Ph.D. with excellent academic credentials along with the track record of scientific productivity evidenced by publications/patents/products in the frontier areas of Plant Biology such as, Computational Biology, Genome Analysis and Molecular Mapping, Molecular Mechanism of Abiotic Stress Responses, Nutritional Genomics, Plant Development and Architecture, Plant Immunity, Molecular Breeding, Transgenics for crop improvement and other emerging areas based on plant genomics.</p>

<p>Remuneration: The length of experience and scientific accomplishments/quality of scientific productivity record will be major factors in deciding the level of appointment as Staff Scientist as well as starting salary in the Pay Bands of Rs 15,600-39,100 (with grade pay of  5400), and Rs 37,400-67,000 (with grade pay of  8,700 and  8,900) plus usual allowances admissible to the Central Government employees. However, NIPGR reserves the right to select candidates in the lower grade against the foregoing posts depending upon the qualifications and experience of the candidate. Reservation of posts shall be as per Govt. of India norms. Five posts (SC-2, ST-1, OBC-2) in the Pay Band of Rs 15,600-39,100 with Grade Pay of  Rs 5400, are reserved.</p>

<p>More at http://www.nipgr.res.in/careers/vacancies_latest.php#</p>

<p>Apply online at http://www.nipgr.res.in/nipgr_recu/nipgr_recu.php</p>

<p>Form http://www.nipgr.res.in/files/careers/Application_Performa_2015.doc</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26453/stacks</guid>
	<pubDate>Wed, 24 Feb 2016 15:52:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26453/stacks</link>
	<title><![CDATA[Stacks]]></title>
	<description><![CDATA[<p>Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.</p>
<p>More at http://catchenlab.life.illinois.edu/stacks/</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/stacks/" rel="nofollow">http://catchenlab.life.illinois.edu/stacks/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/26629/computer-simulation-of-genetic-mechanism</guid>
	<pubDate>Sun, 13 Mar 2016 09:29:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/26629/computer-simulation-of-genetic-mechanism</link>
	<title><![CDATA[Computer simulation of genetic mechanism !!]]></title>
	<description><![CDATA[<p>Computer simulation is the discipline of designing a model of an actual or theoretical physical/biological system, executing the model on a digital computer, and analyzing the execution output. Simulation embodies the principle of ``learning by doing'' --- to learn about the system we must first build a model of some sort and then operate the model. The use of simulation is an activity that is as natural as a child who role plays. Children understand the world around them by simulating (with toys and figurines) most of their interactions with other people, animals and objects. As adults, we lose some of this childlike behavior but recapture it later on through computer simulation. To understand reality and all of its complexity, we must build artificial objects and dynamically act out roles with them. Computer simulation is the electronic equivalent of this type of role playing and it serves to drive synthetic environments and virtual worlds. Within the overall task of simulation, there are three primary sub-fields: model design, model execution and model analysis<br /><br />Simulation models have become important tools in Bioinformatics studies. There are many reasons for this, but we emphasize three of the more important:</p><p>(1) they enable exploration of hypotheses, and as such, have become invaluable means to guide research;</p><p>(2) they are unique approaches to integrate (in the literal term of the word) biological knowledge, in the form of experimental results; and</p><p>(3) they enable connecting biology with other fields of study ranging from physiology to genomics;</p><p>This blog, and this software list, is intended to guide the potential user of simulation models.<br />It is not, in any way, meant to be comprehensive on the very diverse simulation tools that already exist, but focuses on mechanistic, dynamic models. Similarly, it is not meant to provide any coverage of the breadth of applications; however, for interested readers, we provide references to use as a possible starting point.<br /><br />Simulation models are meant to answer questions which scientists have in a dynamic, quantitative, and often, a pictorial way. Much of the bioinformatics research and its applications, in particular, involve a large number of components, actors, and factors. Assembling these in a coherent framework may seem a daunting task, especially for beginners, and can lead to confusion, even for experienced scientists, especially if the objectives of such an exercise are not well defined. Followings are the list of tools bioinformatician may use to analyze and provide answers to complex biological mechanisms and related problems.</p><p style="margin-bottom: 0in;">&nbsp;</p><table width="718" cellspacing="0" cellpadding="2"><colgroup><col width="134"> <col width="501"> </colgroup>
<tbody>
<tr><th style="border: none; padding: 0in;">
<p>Software Resource</p>
</th><th style="border: none; padding: 0in;">
<p>Brief Description and Homepage</p>
</th></tr>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/aladyn/">Aladyn </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Tools to investigate how demographic parameters, populations genetics and abiotic conditions affect the rate of adaptation <br /><a href="http://www.katja-schiffers.eu/research.html">http://www.katja-schiffers.eu/research.html</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/alf/">ALF </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A Simulation Framework for Genome Evolution <br /><a href="http://www.cbrg.ethz.ch/alf">http://www.cbrg.ethz.ch/alf</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/art/">ART </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>ART is a set of simulation tools to generate synthetic next-generation sequencing data by mimicking real sequencing process with empirical error models or quality profiles. <br /><a href="http://www.niehs.nih.gov/research/resources/software/biostatistics/art/">http://www.niehs.nih.gov/research/resources/software/biostatistics/art/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/bamsurgeon/">BAMSurgeon </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Methods for realistic simulation of mutations in real data. <br /><a href="https://github.com/adamewing/bamsurgeon">https://github.com/adamewing/bamsurgeon</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/bayesian-serial-simcoal/">Bayesian Serial SimCoal </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Bayesian Serial SimCoal, (BayeSSC) is a modification of SIMCOAL 1.0, a program written by Laurent Excoffier, John Novembre, and Stefan Schneider. <br /><a href="http://www.stanford.edu/group/hadlylab/ssc/index.html">http://www.stanford.edu/group/hadlylab/ssc/index.html</a></p>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/baysics/">BaySICS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An integral platform with a graphical interface for statistical inference based on approximate Bayesian computation. <br /><a href="https://sites.google.com/site/baysicsabc/">https://sites.google.com/site/baysicsabc/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/beers/">BEERS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>BEERS was designed to benchmark RNA-Seq alignment algorithms and also algorithms that aim to reconstruct different isoforms and alternate splicing from RNA-Seq data <br /><a href="http://cbil.upenn.edu/BEERS/">http://cbil.upenn.edu/beers/</a></p>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/bottleneck/">BOTTLENECK </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Bottleneck is a program for detecting recent effective population size reductions from allele data frequencies <br /><a href="http://www.ensam.inra.fr/URLB/bottleneck/bottleneck.html">http://www.ensam.inra.fr/urlb/bottleneck/bottleneck.html</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/bottlesim/">BottleSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>BottleSim is a computer simulation program for simulating the process of population bottlenecks <br /><a href="http://chkuo.name/software/BottleSim.html">http://chkuo.name/software/bottlesim.html</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/cass/">CASS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Protein Sequence Simulation <br /><a href="https://liberles.cst.temple.edu/Software/CASS/index.html">https://liberles.cst.temple.edu/software/cass/index.html</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/cdpop/">CDPOP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>CDPOP is a landscape genetics tool for simulating the emergence of spatial genetic structure in populations resulting from specified landscape processes governing organism movement behavior. <br /><a href="http://cel.dbs.umt.edu/CDPOP">http://cel.dbs.umt.edu/cdpop</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/classical-genetics-simulator/">Classical Genetics Simulator </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Web-based simulation software <br /><a href="http://www.cgslab.com/">http://www.cgslab.com/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/coasim/">CoaSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>CoaSim is a tool for simulating the coalescent process with recombination and geneconversion under various demographic models. <br /><a href="http://users-birc.au.dk/mailund/CoaSim/index.html">http://users-birc.au.dk/mailund/coasim/index.html</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/cosi/">cosi </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>The cosi package is written in C and is available as a tar file. <br /><a href="http://www.broadinstitute.org/%7Esfs/cosi/">http://www.broadinstitute.org/~sfs/cosi/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/cs-pseq-gen/">CS-PSeq-Gen </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A program to simulate the evolution of protein sequences under the constraints of the information of a particular reconstructed phylogeny <br /><a href="http://bioserv.rpbs.univ-paris-diderot.fr/software/CS-PSeq-Gen/">http://bioserv.rpbs.univ-paris-diderot.fr/software/cs-pseq-gen/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/dawg/">DAWG </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An application designed to simulate the evolution of recombinant DNA sequences in continuous time <br /><a href="http://scit.us/projects/dawg">http://scit.us/projects/dawg</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/easypop/">Easypop </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>EASYPOP is an individual based model intended to simulate datasets under a very broad range of conditions <br /><a href="http://www.unil.ch/dee/en/home/menuinst/softwares--dataset/softwares/easypop.html">http://www.unil.ch/dee/en/home/menuinst/softwares--dataset/softwares/easypop.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/egglib/">EggLib </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>EggLib is a C++/Python library and program package for evolutionary genetics and genomics. <br /><a href="http://egglib.sourceforge.net/">http://egglib.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/episim/">EpiSIM </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>EpiSIM: simulation of multiple epistasis, linkage disequilibrium patterns and haplotype blocks for genome-wide interaction analysis <br /><a href="https://sourceforge.net/projects/episimsimulator/files/">https://sourceforge.net/projects/episimsimulator/files/</a></p>
</td>
</tr>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/evolsimulator/">EvolSimulator </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A simulation test bed for hypotheses of genome evolution <br /><a href="http://acb.qfab.org/acb/evolsim/">http://acb.qfab.org/acb/evolsim/</a></p>
</td>
</tr>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/evolveagene/">EvolveAGene </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A realistic coding sequence simulation program that separates mutation from selection and allows the user to set selection conditions <br /><a href="http://bellinghamresearchinstitute.com/software/index.html">http://bellinghamresearchinstitute.com/software/index.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/fastsimcoal/">fastsimcoal </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A continuous-&shy;‐time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios <br /><a href="http://cmpg.unibe.ch/software/fastsimcoal/">http://cmpg.unibe.ch/software/fastsimcoal/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/fastslink/">FastSLINK </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulation of Marker and Phenotype Data in Pedigrees <br /><a href="https://watson.hgen.pitt.edu/">https://watson.hgen.pitt.edu/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/ffpopsim/">FFPopSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>C++/Python library for population genetics. <br /><a href="http://webdav.tuebingen.mpg.de/ffpopsim/">http://webdav.tuebingen.mpg.de/ffpopsim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/flux-simulator/">FLUX SIMULATOR </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters. <br /><a href="http://sammeth.net/confluence/display/SIM/Home">http://sammeth.net/confluence/display/sim/home</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/forqs/">forqs </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Forward-in-time simulation of Recombination, Quantitative Traits, and Selection <br /><a href="https://bitbucket.org/dkessner/forqs">https://bitbucket.org/dkessner/forqs</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/forsim/">ForSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>ForSim: A Forward Evolutionary Computer Simulation <br /><a href="http://anth.la.psu.edu/research/weiss-lab/research/research">http://anth.la.psu.edu/research/weiss-lab/research/research</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/forwsim/">ForwSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>The program given below is based on the algorithm described in Padhukasahasram et al. 2008 to simulate genetic drift in a standard Wright-Fisher process. <br /><a href="http://badri-populationgeneticsimulators.blogspot.com/">http://badri-populationgeneticsimulators.blogspot.com/</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/fpg/">FPG </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Forward Population Genetic simulation <br /><a href="https://bio.cst.temple.edu/%7Ehey/software/software.htm#FPG">https://bio.cst.temple.edu/~hey/software/software.htm#fpg</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/fregene/">FREGENE </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations. <br /><a href="http://www.ebi.ac.uk/projects/BARGEN">http://www.ebi.ac.uk/projects/bargen</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/frequency-based-insilico-genome-generator-figg/">FIGG </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>FIGG is a genome simulation tool that uses known or theorized variation frequency, per a given fragment size and grouped by GC content across a genome to model new genomes in FASTA format while tracking applied mutations for use in analysis <br /><a href="http://insilicogenome.sourceforge.net/">http://insilicogenome.sourceforge.net/</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/fwdpp/">fwdpp </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A C++ template library for implementing efficient forward simulations. <br /><a href="http://molpopgen.github.io/fwdpp/">http://molpopgen.github.io/fwdpp/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gametes/">GAMETES </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Genetic Architecture Model Emulator for Testing and Evaluating Software: Simulates complex SNP models with pure, strict epistatic interactions with n-loci. <br /><a href="http://sourceforge.net/projects/gametes/?source=navbar">http://sourceforge.net/projects/gametes/?source=navbar</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gasp/">GASP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Genometric Analysis Simulation Program. A software tool for testing and investigating methods in statistical genetics by generating samples of family data based on user specified models. <br /><a href="http://research.nhgri.nih.gov/gasp/">http://research.nhgri.nih.gov/gasp/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gcta/">GCTA </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Genome-wide Complex Trait Analysis <br /><a href="http://www.complextraitgenomics.com/software/gcta/download.html">http://www.complextraitgenomics.com/software/gcta/download.html</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gemsim/">GemSIM </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Next generation sequencing read simulator <br /><a href="http://sourceforge.net/projects/gemsim/">http://sourceforge.net/projects/gemsim/</a></p>
</td>
</tr>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/geneartisan/">GeneArtisan </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulation of Markers in Case-Control Study Designs <br /><a href="http://www.rannala.org/?page_id=241">http://www.rannala.org/?page_id=241</a></p>
</td>
</tr>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/genome/">GENOME </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A rapid coalescent-based whole genome simulator <br /><a href="http://www.sph.umich.edu/csg/liang/genome/">http://www.sph.umich.edu/csg/liang/genome/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/genomepop2/">GenomePop2 </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>GenomePop2 is a specialization of the program GenomePop just to manage SNPs under more flexible and useful settings. If you need models with more than 2 alleles please use the GenomePop program version. <br /><a href="https://ritchielab.psu.edu/research/research-areas/statistical-genetics-and-gen-epi/methods/genomesimla">https://ritchielab.psu.edu/research/research-areas/statistical-genetics-and-gen-epi/methods/genomesimla</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/genomesimla/">GenomeSimla </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>GenomeSIMLA is currently under development- however, we have a beta release that we are asking to be tested <br /><a href="http://chgr.mc.vanderbilt.edu/genomeSIMLA/">http://chgr.mc.vanderbilt.edu/genomesimla/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gens2/">GENS2 </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. <br /><a href="https://sourceforge.net/projects/gensim/">https://sourceforge.net/projects/gensim/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/gwasimulator/">GWAsimulator </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A rapid whole genome simulation program <br /><a href="http://biostat.mc.vanderbilt.edu/wiki/Main/GWAsimulator">http://biostat.mc.vanderbilt.edu/wiki/main/gwasimulator</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/hap-sample/">HAP-SAMPLE </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An association simulator for candidate regions or genome scans <br /><a href="http://www.hapsample.org/">http://www.hapsample.org/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/hapgen/">HAPGEN </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A simulator for the simulation of case control datasets at SNP markers <br /><a href="https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html">https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html</a></p>
</td>
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<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/hapsim/">HapSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients <br /><a href="http://cran.r-project.org/web/packages/hapsim/index.html">http://cran.r-project.org/web/packages/hapsim/index.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/hapsimu/">HAPSIMU </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A program that simulates heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model <br /><a href="http://l.web.umkc.edu/liujian/">http://l.web.umkc.edu/liujian/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/ibdsim/">IBDsim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>IBDSim is a computer package for the simulation of genotypic data under general isolation by distance models. <br /><a href="http://raphael.leblois.free.fr/">http://raphael.leblois.free.fr/</a></p>
</td>
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<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/indel-seq-gen/">indel-Seq-Gen </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A biological sequence simulation program that simulates highly divergent DNA sequences and protein superfamilies <br /><a href="http://bioinfolab.unl.edu/%7Ecstrope/iSG/">http://bioinfolab.unl.edu/~cstrope/isg/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/indelible/">Indelible </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A powerful and flexible simulator of biological evolution <br /><a href="http://abacus.gene.ucl.ac.uk/software/indelible/">http://abacus.gene.ucl.ac.uk/software/indelible/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/invertfregene/">invertFREGENE </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>InvertFREGENE is a forward-in-time simulator of inversions in population genetic data <br /><a href="http://www.ebi.ac.uk/projects/BARGEN/">http://www.ebi.ac.uk/projects/bargen/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/kernalpop/">kernalPop </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A spatially explicit population genetic simulation engine <br /><a href="http://cran.r-project.org/src/contrib/Archive/kernelPop/">http://cran.r-project.org/src/contrib/archive/kernelpop/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/macs/">MaCS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Markovian Coalescent Simulator <br /><a href="http://www-hsc.usc.edu/%7Egarykche/">http://www-hsc.usc.edu/~garykche/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/marlin/">Marlin </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Marlin provides a user-friendly interface for performing forward-in-time population genetic simulations. <br /><a href="http://www.patrickmeirmans.com/software/Marlin.html">http://www.patrickmeirmans.com/software/marlin.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/mason/">Mason </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A package for the simulation of nucleotide data. <br /><a href="http://www.seqan.de/projects/mason/">http://www.seqan.de/projects/mason/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/mbs/">mbs </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection <br /><a href="http://www.sendou.soken.ac.jp/esb/innan/InnanLab/software.html">http://www.sendou.soken.ac.jp/esb/innan/innanlab/software.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/mendels-accountant/">Mendel's Accountant </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Mendel's Accountant (MENDEL) is an advanced numerical simulation program for modeling genetic change over time and was developed collaboratively by Sanford, Baumgardner, Brewer, Gibson and ReMine <br /><a href="http://mendelsaccount.sourceforge.net/">http://mendelsaccount.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/metapopgen/">MetaPopGen </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulates genetics in large size metapopulations <br /><a href="https://sites.google.com/site/marcoandrello/metapopgen">https://sites.google.com/site/marcoandrello/metapopgen</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/metasim/">MetaSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A tool to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets <br /><a href="http://ab.inf.uni-tuebingen.de/software/metasim/">http://ab.inf.uni-tuebingen.de/software/metasim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/mlcoalsim/">mlcoalsim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Multilocus Coalescent Simulations <br /><a href="http://code.google.com/p/mlcoalsim-v1/">http://code.google.com/p/mlcoalsim-v1/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/ms/">ms </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br /><a href="http://home.uchicago.edu/%7Erhudson1/source/mksamples.html">http://home.uchicago.edu/~rhudson1/source/mksamples.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/mshot/">msHOT </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br /><a href="http://home.uchicago.edu/%7Erhudson1/">http://home.uchicago.edu/~rhudson1/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/msms/">msms </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A coalescent Simlation tool with selection. <br /><a href="http://www.mabs.at/ewing/msms/index.shtml">http://www.mabs.at/ewing/msms/index.shtml</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/myssp/">MySSP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A program for the simulation of DNA sequence evolution across a phylogenetic tree <br /><a href="http://www.rosenberglab.net/software.html">http://www.rosenberglab.net/software.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/nemo/">Nemo </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A forward-time, individual-based, genetically explicit, and stochastic simulation program designed to study the evolution of genetic markers, life history traits, and phenotypic traits in a flexible (meta-)population framework. <br /><a href="http://nemo2.sourceforge.net/">http://nemo2.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/netrecodon/">NetRecodon </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Coalescent simulation of coding DNA sequences with recombination (inter and intracodon), migration and demography <br /><a href="http://code.google.com/p/netrecodon/">http://code.google.com/p/netrecodon/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/oncosimulr/">OncoSimulR </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>BioConductor package for Forward Genetic Simulation of Cancer Progresion with Epistasis <br /><a href="https://github.com/rdiaz02/OncoSimul">https://github.com/rdiaz02/oncosimul</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/pedagog/">PEDAGOG </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Software for simulating eco-evolutionary population dynamics <br /><a href="https://bcrc.bio.umass.edu/pedigreesoftware/node/5">https://bcrc.bio.umass.edu/pedigreesoftware/node/5</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/phenosim/">phenosim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A tool to add phenotypes to simulated genotypes <br /><a href="http://evoplant.uni-hohenheim.de/doku.php?id=software:software">http://evoplant.uni-hohenheim.de/doku.php?id=software:software</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/phylosim/">PhyloSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An R package for the Monte Carlo simulation of sequence evolution <br /><a href="http://www.ebi.ac.uk/goldman-srv/phylosim/">http://www.ebi.ac.uk/goldman-srv/phylosim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/pirs/">pIRS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Profile-based Illumina pair-end reads simulator <br /><a href="https://code.google.com/p/pirs/">https://code.google.com/p/pirs/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/proteinevolver/">ProteinEvolver </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulation of protein evolution along phylogenies under structure-based substitution models <br /><a href="http://code.google.com/p/proteinevolver/">http://code.google.com/p/proteinevolver/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/qmsim/">QMSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>QTL and Marker Simulator <br /><a href="http://www.aps.uoguelph.ca/%7Emsargol/qmsim/">http://www.aps.uoguelph.ca/~msargol/qmsim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/quantinemo/">quantiNEMO </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An individual-based program for the analysis of quantitative traits with explicit genetic architecture potentially under selection in a structured population <br /><a href="http://www2.unil.ch/popgen/softwares/quantinemo/">http://www2.unil.ch/popgen/softwares/quantinemo/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/recoal/">RECOAL </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulates new haplotype data from a reference population of haplotypes. <br /><a href="ftp://popgen.usc.edu/">ftp://popgen.usc.edu/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/recodon/">Recodon </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Coalescent simulation of coding DNA sequences with recombination, migration and demography <br /><a href="http://code.google.com/p/recodon/">http://code.google.com/p/recodon/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/rlsim/">rlsim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A package for simulating RNA-seq library preparation with parameter estimation <br /><a href="http://bit.ly/rlsim-git">http://bit.ly/rlsim-git</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/rmetasim/">Rmetasim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Rmetasim is a front-end for the metasim engine that is implemented as a package that runs in the statistical computing environment R <br /><a href="http://cran.r-project.org/web/packages/rmetasim/index.html">http://cran.r-project.org/web/packages/rmetasim/index.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/rna-seq-simulator/">RNA Seq Simulator </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>RSS takes SAM alignment files from RNA-Seq data and simulates over dispersed, multiple replica, differential, non-stranded RNA-Seq datasets. <br /><a href="http://useq.sourceforge.net/cmdLnMenus.html#RNASeqSimulator">http://useq.sourceforge.net/cmdlnmenus.html#rnaseqsimulator</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/rose/">Rose </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Random model of sequence evolution <br /><a href="http://bibiserv.techfak.uni-bielefeld.de/rose/">http://bibiserv.techfak.uni-bielefeld.de/rose/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/scrm/">scrm </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A coalescent simulator optimized for long sequences and large samples. <br /><a href="https://scrm.github.io/">https://scrm.github.io/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/selsim/">SelSim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recom- bining region within which a single bi-allelic site has experienced natural selection <br /><a href="http://www.well.ox.ac.uk/%7Espencer/SelSim/">http://www.well.ox.ac.uk/~spencer/selsim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/seq-gen/">Seq-Gen </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees. <br /><a href="http://tree.bio.ed.ac.uk/software/seqgen/">http://tree.bio.ed.ac.uk/software/seqgen/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/seqpower/">SEQPower </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Statistical power analysis for sequence-based association studies <br /><a href="http://bioinformatics.org/spower/">http://bioinformatics.org/spower/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/seqsimla/">SeqSIMLA </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated. <br /><a href="http://seqsimla.sourceforge.net/">http://seqsimla.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/serial-netevolve/">Serial NetEvolve </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A flexible utility for generating serially-sampled sequences along a tree or recombinant network <br /><a href="http://biorg.cis.fiu.edu/SNE/">http://biorg.cis.fiu.edu/sne/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/sfs_code/">SFS_CODE </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SFS_CODE can perform forward population genetic simulations under a general Wright-Fisher model with arbitrary migration, demographic, selective, and mutational effects. <br /><a href="http://sfscode.sourceforge.net/SFS_CODE/index/index.html">http://sfscode.sourceforge.net/sfs_code/index/index.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/sibsim/">SIBSIM </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Quantitative phenotype simulation in extended pedigrees <br /><a href="http://sourceforge.net/projects/sibsim/">http://sourceforge.net/projects/sibsim/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simadapt/">SimAdapt </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A spatially explicit, individual-based, forward-time, landscape-genetic simulation model combined with a landscape cellular automaton. <br /><a href="https://www.openabm.org/model/3137">https://www.openabm.org/model/3137</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simcoal2/">SIMCOAL2 </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A coalescent program for the simulation of complex recombination patterns over large genomic regions under various demographic models <br /><a href="http://cmpg.unibe.ch/software/simcoal2/">http://cmpg.unibe.ch/software/simcoal2/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simcopy/">SimCopy </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>An R package simulating the evolution of copy number profiles along a tree. <br /><a href="http://bit.ly/simcopy">http://bit.ly/simcopy</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simla/">SIMLA </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SIMLA is a SIMuLAtion program that generates data sets of families for use in Linkage and Association studies. <br /><a href="http://dmpi.duke.edu/simla-simulation-software-version-32">http://dmpi.duke.edu/simla-simulation-software-version-32</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simped/">SimPed </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A Simulation Program to Generate Haplotype and Genotype Data for Pedigree Structures <br /><a href="http://bioinformatics.org/simped/">http://bioinformatics.org/simped/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simprot/">Simprot </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A program to simulate protein evolution by substitution, insertion and deletion <br /><a href="http://www.uhnresearch.ca/labs/tillier/software.htm#3">http://www.uhnresearch.ca/labs/tillier/software.htm#3</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simrare/">SimRare </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Rare variant simulation and analysis tool <br /><a href="http://code.google.com/p/simrare/">http://code.google.com/p/simrare/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simugwas/">simuGWAS </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A forward-time simulator that simulates realistic samples for genome-wide association studies. <br /><a href="http://simupop.sourceforge.net/Cookbook/SimuGWAS">http://simupop.sourceforge.net/cookbook/simugwas</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/simupop/">simuPOP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>simuPOP is a general-purpose individual-based forward-time population genetics simulation environment. <br /><a href="http://simupop.sourceforge.net/">http://simupop.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/sissi/">SISSI </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A software tool to generate data of related sequences along a given phylogeny, taking into account user defined system of neighbourhoods and instantaneous rate matrices. <br /><a href="http://www.cibiv.at/software/sissi/">http://www.cibiv.at/software/sissi/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/smartpop/">SMARTPOP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulating Mating Alliance as a Reproductive Tactic for Populations <br /><a href="http://smartpop.sourceforge.net/">http://smartpop.sourceforge.net/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/snpsim/">SNPsim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Coalescent simulation of hotspot recombination <br /><a href="http://code.google.com/p/phylosoftware/">http://code.google.com/p/phylosoftware/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/spip/">SPIP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SPIP simulates the transmission of genes from parents to offspring in a population having demographic structure defined by the user <br /><a href="http://swfsc.noaa.gov/textblock.aspx?Division=FED&amp;id=3434">http://swfsc.noaa.gov/textblock.aspx?division=fed&amp;id=3434</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/splatche/">Splatche </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Spatial and Temporal Coalescences in Heterogeneous Environment <br /><a href="http://www.splatche.com/">http://www.splatche.com/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/srv/">srv </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Simulator of Rare Varaints (srv) is a simulator for the simulation of the introduction and evolution of (rare) genetic variants. <br /><a href="http://simupop.sourceforge.net/Cookbook/SimuRareVariants">http://simupop.sourceforge.net/cookbook/simurarevariants</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/sup/">SUP </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>SLINK/FastSLINK utility program <br /><a href="http://mlemire.freeshell.org/software.html">http://mlemire.freeshell.org/software.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/treesimj/">TreesimJ </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A flexible, forward-time population genetic simulator <br /><a href="http://code.google.com/p/treesimj/">http://code.google.com/p/treesimj/</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/variant-simulation-tools/">Variant Simulation Tools </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>A simulation tool for post-GWAS genetic epidemiological studies using whole-genome or whole-exome next-gen sequencing data, with an emphasis on user-friendliness and reproducibility. <br /><a href="http://varianttools.sourceforge.net/Simulation/HomePage">http://varianttools.sourceforge.net/simulation/homepage</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/vortex/">Vortex </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>VORTEX is an individual-based simulation model for population viability analysis (PVA). <br /><a href="http://www.vortex9.org/vortex.html">http://www.vortex9.org/vortex.html</a></p>
</td>
</tr>
<tr><th style="border: none; padding: 0in;">
<p><a href="https://popmodels.cancercontrol.cancer.gov/gsr/packages/wessim/">Wessim </a></p>
</th>
<td style="border: none; padding: 0in;">
<p>Whole Exome Sequencing SIMulator <br /><a href="http://sak042.github.io/Wessim/">http://sak042.github.io/wessim/</a></p>
</td>
</tr>
</tbody>
</table><p style="margin-bottom: 0in;">&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</guid>
	<pubDate>Tue, 26 Apr 2016 03:50:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27080/mrfast-micro-read-fast-alignment-search-tool</link>
	<title><![CDATA[mrFAST:  Micro Read Fast Alignment Search Tool]]></title>
	<description><![CDATA[<p><span>mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find&nbsp;</span><strong><span style="text-decoration: underline;">'all'</span></strong><span>&nbsp; mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.</span></p>
<p><span>More at&nbsp;http://mrfast.sourceforge.net/manual.html</span></p><p>Address of the bookmark: <a href="http://mrfast.sourceforge.net/manual.html" rel="nofollow">http://mrfast.sourceforge.net/manual.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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