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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44904?offset=50</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</guid>
	<pubDate>Fri, 13 May 2016 05:25:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27333/satsuma-highly-sensitive-whole-genome-synteny-alignments</link>
	<title><![CDATA[SATSUMA : Highly sensitive whole-genome synteny alignments.]]></title>
	<description><![CDATA[<p>Satsuma is a whole-genome synteny alignment program. It takes two genomes, computes alignments, and then keeps only the parts that are orthologous, i.e. following the conserved order and orientation of features, such as protein coding genes, non-coding genes, or neutral sequences. Satsuma does not require any pre-processing, such as repeat masking, since it will automatically detect ambiguous mappings.<br> <br> Satsuma has parallelization built-in and is designed to run on multi-core architectures. The run-time for aligning two bird-size genomes (~1.2 Gb) is around two days on 24 CPUs. <br> <br> You can find the manual <a href="http://satsuma.sourceforge.net/manual.html">here</a>.<br> Download the latest source code from <a href="https://sourceforge.net/projects/satsuma/">here.</a><br> Stable versions can also be downloaded from the <a href="https://www.broadinstitute.org/science/programs/genome-biology/spines">Broad Institute's</a> web site.<br> <br> An incomplete list of questions and answers (yes, these have really been asked by our users! Please feel free to add your own by e-mailing us) is <a href="http://satsuma.sourceforge.net/faq.html">here</a>.<br> <br> If you use Satsuma in your research, please cite:<br> <a href="http://bioinformatics.oxfordjournals.org/content/26/9/1145.long">Grabherr, M. G., Russell, P., Meyer, M., Mauceli, E., Alf&ouml;ldi, J., Di Palma, F., &amp; Lindblad-Toh, K. (2010). Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics, 26(9), 1145-51</a>.</p>
<p><strong>Tutorial at http://evomics.org/learning/genomics/satsuma/</strong></p><p>Address of the bookmark: <a href="http://satsuma.sourceforge.net/" rel="nofollow">http://satsuma.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30111/eager</guid>
	<pubDate>Sat, 10 Dec 2016 18:07:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30111/eager</link>
	<title><![CDATA[EAGER]]></title>
	<description><![CDATA[<p><span>The automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process.</span></p>
<p><span>EAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.</span></p>
<p>https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0918-z</p><p>Address of the bookmark: <a href="https://github.com/apeltzer/EAGER-GUI" rel="nofollow">https://github.com/apeltzer/EAGER-GUI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</guid>
	<pubDate>Sun, 06 Aug 2017 06:58:12 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34088/sequence-evolution-function-computational-approaches-in-comparative-genomics</link>
	<title><![CDATA[Sequence - Evolution - Function; Computational Approaches in Comparative Genomics]]></title>
	<description><![CDATA[<p><em>Sequence - Evolution - Function</em><span>&nbsp;is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/books/NBK20260/" rel="nofollow">https://www.ncbi.nlm.nih.gov/books/NBK20260/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</guid>
	<pubDate>Thu, 25 Oct 2018 06:14:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37993/platypus-a-haplotype-based-variant-caller-for-next-generation-sequence-data</link>
	<title><![CDATA[Platypus: A Haplotype-Based Variant Caller For Next Generation Sequence Data]]></title>
	<description><![CDATA[<p><strong>Platypus</strong><span>&nbsp;is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect SNPs, MNPs, short indels, replacements and (using the assembly option) deletions up to several kb. It has been extensively tested on&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/?term=24463883">whole-genome</a><span>,&nbsp;</span><a href="http://www.nature.com/ng/journal/v45/n1/abs/ng.2492.html">exon-capture</a><span>, and&nbsp;</span><a href="http://www.nature.com/nature/journal/v493/n7432/abs/nature11725.html">targeted capture</a><span>&nbsp;data, it has been run on very large datasets as part of the&nbsp;</span><a href="http://www.1000genomes.org/">Thousand Genomes</a><span>&nbsp;and WGS500 projects, and is being used in clinical sequencing trials in the&nbsp;</span><a href="http://www.mcgprogramme.com/">Mainstreaming Cancer Genetics</a><span>&nbsp;programme.&nbsp;</span></p>
<p><span>Tutorial&nbsp;https://github.com/andyrimmer/Platypus/blob/master/misc/README.txt</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/platypus" rel="nofollow">http://www.well.ox.ac.uk/platypus</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</guid>
	<pubDate>Wed, 25 Nov 2020 19:51:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42359/dnasp-dna-sequence-polymorphism-is-a-software-package-for-the-analysis-of-dna-polymorphisms</link>
	<title><![CDATA[DnaSP: DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms]]></title>
	<description><![CDATA[<p><span>DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some assembler RAD-seq software). DnaSP can estimate several measures of DNA sequence variation within and between populations in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters.</span></p><p>Address of the bookmark: <a href="http://www.ub.edu/dnasp/" rel="nofollow">http://www.ub.edu/dnasp/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</guid>
	<pubDate>Sat, 08 Jun 2024 16:03:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44555/ultra-ultra-locates-tandemly-repetitive-areas-effective-labeling-of-repetitive-genomic-sequence</link>
	<title><![CDATA[ULTRA (ULTRA Locates Tandemly Repetitive Areas) : Effective Labeling of Repetitive Genomic Sequence]]></title>
	<description><![CDATA[<p dir="auto">ULTRA is a tool to find and annotate tandem repeats inside genomic sequence. It is able to find repeats of any length and of any period (up to a maximum period of 4000). It can find highly decayed repeats missed by other software, and it will also be able to find very large repeats in highly repetitive sequence, regardless of the size of sequence or length of repeats. ULTRA offers meaningful annotation scores and can produce annotation P-values at user request.</p>
<p dir="auto">More at&nbsp;https://www.biorxiv.org/content/10.1101/2024.06.03.597269v1</p><p>Address of the bookmark: <a href="https://github.com/TravisWheelerLab/ULTRA" rel="nofollow">https://github.com/TravisWheelerLab/ULTRA</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36921/breakpointer-using-local-mapping-artifacts-to-support-sequence-breakpoint-discovery-from-single-end-reads</guid>
	<pubDate>Tue, 12 Jun 2018 12:41:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36921/breakpointer-using-local-mapping-artifacts-to-support-sequence-breakpoint-discovery-from-single-end-reads</link>
	<title><![CDATA[Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads]]></title>
	<description><![CDATA[Breakpointer is a fast tool for locating sequence breakpoints from the alignment of single end reads (SE) produced by next generation sequencing (NGS). It adopts a heuristic method in searching for local mapping signatures created by insertion/deletions (indels) or more complex structural variants(SVs).<p>Address of the bookmark: <a href="https://github.com/ruping/Breakpointer" rel="nofollow">https://github.com/ruping/Breakpointer</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</guid>
	<pubDate>Fri, 09 Nov 2018 13:34:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</link>
	<title><![CDATA[AMStat: display statistics of large sequence files from next generation sequencing projects]]></title>
	<description><![CDATA[<p><span>SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to&nbsp;</span><a href="http://samstat.sourceforge.net/#about">SAM/BAM</a><span>&nbsp;files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.</span></p><p>Address of the bookmark: <a href="http://samstat.sourceforge.net/" rel="nofollow">http://samstat.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</guid>
	<pubDate>Tue, 20 Aug 2019 09:47:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39856/tritex-sequence-assembly-pipeline-for-triticeae-genomes</link>
	<title><![CDATA[TRITEX sequence assembly pipeline for Triticeae genomes]]></title>
	<description><![CDATA[<div>
<p>The pipeline is open-source and hosted in a public Bitbucket&nbsp;<a href="https://bitbucket.org/tritexassembly/tritexassembly.bitbucket.io/src/master/">repository</a>.</p>
</div>
<div>
<p>TRITEX has been run on highly inbred genotypes of barley (<em>Hordeum vulgare</em>), tetraploid wheat (<em>Triticum turgidum</em>) and hexaploid wheat (<em>T. aestivum</em>) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.</p>
</div>
<div>
<p>A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in&nbsp;<a href="https://bio-protocol.org/e2955">Himmelbach et al. 2018</a>. Refer to the&nbsp;<a href="https://www.10xgenomics.com/resources/technical-notes/">technical notes</a>&nbsp;of 10X Genomics on how to generate Chromium data.</p>
</div><p>Address of the bookmark: <a href="https://tritexassembly.bitbucket.io/" rel="nofollow">https://tritexassembly.bitbucket.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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