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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40598?offset=510</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</guid>
	<pubDate>Tue, 04 Aug 2015 05:14:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/poll/view/23590/will-minion-nanopore-sequencing-increase-the-number-of-next-generation-sequencing-projects</link>
	<title><![CDATA[Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?]]></title>
	<description><![CDATA[<p>Will MinION Nanopore sequencing increase the number of Next Generation Sequencing projects?</p>]]></description>
	<dc:creator>Strand</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</guid>
	<pubDate>Mon, 08 Feb 2016 15:39:04 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26319/n50plottingtools</link>
	<title><![CDATA[n50PlottingTools]]></title>
	<description><![CDATA[<p><span>Tools to create plots showing N-statistics for genome assemblies </span></p>
<p><span>More at https://github.com/dentearl/n50PlottingTools</span></p><p>Address of the bookmark: <a href="https://github.com/dentearl/n50PlottingTools" rel="nofollow">https://github.com/dentearl/n50PlottingTools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/26828/bioinfolab</guid>
  <pubDate>Fri, 25 Mar 2016 11:05:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[BioinfoLab]]></title>
  <description><![CDATA[
<p>Laboratory of Statistics and Computational tools for Bioinformatics</p>

<p>The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&amp;C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments. </p>

<p>More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</guid>
	<pubDate>Tue, 26 Apr 2016 03:48:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis</link>
	<title><![CDATA[HOMER:  Software for motif discovery and next-gen sequencing analysis]]></title>
	<description><![CDATA[<p><span>This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/computerSetup.html">Setting up your computing environment</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/retrieveFiles.html">Retrieving and storing sequencing files</a>&nbsp;(your own data or from public sources)</li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/fastqFiles.html">Checking sequence quality, trimming, general sequence manipulation</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/mapping.html">Mapping reads to a reference genome</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/samfiles.html">Manipulating SAM/BAM alignment files</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/genomeBrowsers.html">Visualizing data in a genome browser</a></li>
</ol>
<p><br>RNA-Seq</p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqCufflinks.html">De novo transcript discovery and differential analysis with Cufflinks</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/rnaseqR.html">Differential expression analysis with R/Bioconductor</a></li>
<li><a href="http://homer.salk.edu/homer/basicTutorial/clustering.html">Clustering of large expression datasets (microarray or RNA-Seq)</a></li>
</ol>
<p><br><span>Microarray</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/affymetrix.html">Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor</a></li>
</ol>
<p><span>General Tips for Data Analysis</span></p>
<ol>
<li><a href="http://homer.salk.edu/homer/basicTutorial/excelTips.html">Excel workarounds, adding gene annotation, X-Y plots tips, etc.</a></li>
</ol><p>Address of the bookmark: <a href="http://homer.salk.edu/homer/basicTutorial/" rel="nofollow">http://homer.salk.edu/homer/basicTutorial/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28112/ngs-glossary</guid>
	<pubDate>Mon, 27 Jun 2016 08:56:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28112/ngs-glossary</link>
	<title><![CDATA[NGS Glossary !!]]></title>
	<description><![CDATA[<p><strong>alignment</strong>: the mapping of a raw sequence read to a location within a reference genome. The mapping occurs because the sequences within the raw read match or align to sequences within the reference genome. Alignment information is stored in the <strong>SAM</strong> or <strong>BAM</strong> file formats.</p><p><strong>bcftools</strong>: a set of companion tools, currently bundled with SAMtools, for identifying and filtering genomics variants.</p><p><strong>bowtie</strong>: widely used, open source alignment software for aligning raw sequence reads to a reference genome.</p><p><strong>BAM Format</strong>: binary, compressed format for storing <strong>SAM</strong> data.</p><p><strong>BCF Format</strong>: Binary call format. Binary, compressed format for storing <strong>VCF</strong> data.</p><p><strong>CIGAR String</strong>: Compact Idiosyncratic Gapped Alignment Report. A compact string that (partially) summarizes the alignment of a raw sequence read to the reference genome. Three core abbreviations are used: M for alignment match; I for insertion; and D for Deletion. For example, a CIGAR string of 5M2I63M indicates that the first 5 base pairs of the read align to the reference, followed by 2 base pairs, which are unique to the read, and not in the reference genome, followed by an additional 63 base pairs of alignment.</p><p><strong>FASTA Format</strong>: text format for storing raw sequence data. For example, the FASTA file at: <a href="http://www.ncbi.nlm.nih.gov/nuccore/NC_008253">http://www.ncbi.nlm.nih.gov/nuccore/NC_008253</a> contains entire genome for Escherichia coli 536.</p><p><strong>FASTQ Format</strong>: text format for storing raw sequence data along with quality scores for each base; usually generated by sequencing machines.</p><p><strong>genotype likelihood</strong>: the probability that a specific genotype is present in the sample of interest. Genotype likelihoods are usually expressed as a <strong>Phred-scaled probability</strong>, where P = 10 ^ (-Q/10). For example, if the genotype TT (both alleles are T) at position 1,299,132 in human chromosome 12 (reference G) is 37, this translates to a probability of 10<sup>-37/10</sup> = 0.0001995, meaning that there is very low probability that the reads in your sample support a TT genotype. On the other hand, a genotype of AA at the same position with a score of 0 translates into a probability of 10<sup>-0</sup> = 1, indicating extremely high probability that your sample contains a homozygous mutation of G to A.</p><p><strong>mate-pair</strong>: in paired-end sequencing, both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. The two ends which are sequenced form a pair, and are frequently referred to as mate-pairs.</p><p><strong>QNAME</strong>: unique identifier of a raw sequence read (also known as the Query Name). Used in <strong>FASTQ</strong> and <strong>SAM</strong> files.</p><p><strong>paired-end sequencing</strong>: sequencing process where both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. Particularly useful for identifying structural rearrangements, including gene fusions.</p><p><strong>Phred-scaled probability</strong>: a scaled value (Q) used to compactly summarize a probability, where P = 10<sup>-Q/10</sup>. For example, a Phred Q score of 10 translates to probability (P) = 10<sup>-10/10</sup> = 0.1. Phred-scaled probabilities are common in next-generation sequencing, and are used to represent multiple types of quality metrics, including quality of base calls, quality of mappings, and probabilities associated with specific genotypes. The name Phred refers to the original Phred base-calling software, which first used and developed the scale.</p><p><strong>Phred quality score</strong>: a score assigned to each base within a sequence, quantifying the probability that the base was called incorrectly. Scores use a <strong>Phred-scaled probability</strong> metric. For example, a Phred Q score of 10 translates to P=10<sup>-10/10</sup> = 0.1, indicating that the base has a 0.1 probability of being incorrect. Higher Phred score correspond to higher accuracy. In the <strong>FASTQ format</strong>, Phred scores are represented as single ASCII letters. For details on translating between Phred scores and ASCII values, refer to <a href="http://www.somewhereville.com/?p=1508">Table 1 of this useful blog post from Damian Gregory Allis</a>.</p><p><strong>read-length</strong>: the number of base pairs that are sequenced in an individual sequence read.</p><p><strong>read-depth</strong>: the number of sequence reads that pile up at the same genomic location. For example, 30X read-depth coverage indicates that the genomic location is covered by 30 independent sequencing reads. Increased read-depth translates into higher confidence for calling genomic variants.</p><p><strong>RNAME</strong>: reference genome identifier (also known as the Reference Name). Within a SAM formatted file, the RNAME identifies the reference genome where the raw read aligns.</p><p><strong>SAM Flag</strong>: a single integer value (e.g. 16), which encodes multiple elements of meta-data regarding a read and its alignment. Elements include: whether the read is one part of a paired-end read, whether the read aligns to the genome, and whether the read aligns to the forward or reverse strand of the genome. A <a href="http://picard.sourceforge.net/explain-flags.html">useful online utility</a> decodes a single SAM flag value into plain English.</p><p><strong>SAM Format</strong>: Text file format for storing sequence alignments against a reference genome. See also <strong>BAM</strong> Format.</p><p><strong>SAMtools</strong>: widely used, open source command line tool for manipulating SAM/BAM files. Includes options for converting, sorting, indexing and viewing SAM/BAM files. The SAMtools distribution also includes bcftools, a set of command line tools for identifying and filtering genomics variants. Created by <a href="http://lh3lh3.users.sourceforge.net/">Heng Li</a>, currently of the Broad Institute.</p><p><strong>single-read sequencing</strong>: sequencing process where only one end of a DNA or RNA fragment is sequenced. Contrast with <strong>paired-end</strong> sequencing.</p><p><strong>VCF Format</strong>: Variant call format. Text file format for storing genomic variants, including single nucleotide polymorphisms, insertions, deletions and structural rearrangements. See also <strong>BCF</strong> format.</p><p><strong>Next</strong><strong>Generation</strong><strong>Sequencing</strong><br /> A high-throughput sequencing method which parallelizes the sequencing process, producing thousands or millions of sequences at once.</p><p><strong>Deep</strong><strong>Sequencing</strong><br /> Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced.</p><p><strong>Paired-End</strong><strong>Sequencing</strong><br /> Sequence both ends of the same fragment and keep track of the paired data.</p><p><strong>Adapter</strong><br /> Short oligonucleotides which are attached to the DNA to be sequenced. An adapter can provide a priming site for both amplification and sequencing of the adjoining, unknown nucleic acid.</p><p><strong>Library</strong><br /> A collection of DNA fragments with adapters ligated to each end.</p><p><strong>Bridge</strong><strong>Amplification</strong><br /> Generation of in situ copies of a specific DNA molecule on an oligo-decorated solid support.</p><p><strong>Emulsion</strong><strong>PCR</strong><br /> A method for bead-based amplification of a library. A single adapter-bound fragment is attached to the surface of a bead, and an oil emulsion containing necessary amplification reagents is formed around the bead/fragment component. Parallel amplification of millions of beads with millions of single strand fragments produces a sequencer-ready library.</p><p><strong>Alignment</strong><br /> Mapping of sequence reads to a known reference sequence</p><p><strong>Reference</strong><strong>sequence</strong><strong>/</strong><strong>genome</strong><strong>&nbsp; </strong><br /> A fully assembled version of a genome that can be used for mapping short DNA sequence reads for comparisons of genomes from various individuals</p><p><strong>Coverage</strong><strong>Depth</strong><br /> The number of nucleotides from reads that are mapped to a given position of reference genome.</p><p><strong>Specificity</strong><strong>&nbsp; </strong><br /> The percentage of sequences that map to the intended targets out of total bases per run.</p><p><strong>Uniformity</strong><strong>&nbsp; </strong><br /> The variability in sequence coverage across target regions.</p><p><strong>Homopolymer</strong><br /> Uninterrupted stretch of a single nucleotide type (e.g., TTT or GGGGGG)</p><p><strong>InDel</strong><br /> InDel stands for Insertion or deletion. A form of structural variation in which a DNA segment is either deleted or inserted.</p><p><strong>SNP</strong><strong>&nbsp; </strong></p><p>SNP stands for Single Nucleotide Polymorphism. A single base difference found when comparing the same DNA sequence from two different individuals.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28554/megan6</guid>
	<pubDate>Mon, 25 Jul 2016 05:45:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28554/megan6</link>
	<title><![CDATA[MEGAN6]]></title>
	<description><![CDATA[<p>Microbiome analysis using a single application</p>
<p>MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.</p>
<ul>
<li>Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA</li>
<li>Functional analysis using InterPro2GO, SEED, eggNOG or KEGG</li>
<li>Bar charts, word clouds, Voronoi tree maps and many other charts</li>
<li>PCoA, clustering and networks</li>
<li>Supports metadata</li>
<li>MEGAN parses many different types of input</li>
</ul>
<p>Why use MEGAN6?</p>
<div>&nbsp;The software is:</div>
<div><ol>
<li>Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.</li>
<li>Powerful. MEGAN6 allows you to work with hundreds of samples containing&nbsp;hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.</li>
<li>Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.</li>
</ol></div><p>Address of the bookmark: <a href="https://ab.inf.uni-tuebingen.de/software/megan6" rel="nofollow">https://ab.inf.uni-tuebingen.de/software/megan6</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</guid>
	<pubDate>Fri, 28 Oct 2016 07:59:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29583/graph-genome-suite</link>
	<title><![CDATA[Graph Genome Suite]]></title>
	<description><![CDATA[<p><span>Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the&nbsp;</span><strong>Graph Genome Suite</strong><span>&nbsp;&mdash; the most advanced population genomics tools in the world.</span></p><p>Address of the bookmark: <a href="https://www.sbgenomics.com/graph/" rel="nofollow">https://www.sbgenomics.com/graph/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</guid>
	<pubDate>Fri, 04 Nov 2016 12:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</link>
	<title><![CDATA[R Graphical Cookbook by Winston Chang]]></title>
	<description><![CDATA[<p>R Graphical Cookbook by Winston Chang</p><p>A very nice book by Winston Chang for R ethusiast. The R code presented in these pages is the R code actually used to produce the Figures in the book. There will be differences compared to the code chunks shown in the text of the book, but in most cases the differences will be that these pages contain additional code to lay out multiple plots on a single "page".</p><p>The code presented for each figure is self-contained, i.e., all code required to produce the figure is included. This means that there is sometimes considerable overlap of code between several figures  In some cases, it may be necessary to install an add-on package from CRAN to get the code to run.</p><p>More books at http://www.e-reading.club/bookreader.php/137370/C486x_APPb.pdf</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29638" length="37521" type="image/png" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</guid>
	<pubDate>Thu, 08 Dec 2016 09:31:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30085/fqtools</link>
	<title><![CDATA[fqtools]]></title>
	<description><![CDATA[<p><code>fqtools</code><span>&nbsp;is a software suite for fast processing of&nbsp;</span><code>FASTQ</code><span>&nbsp;files. Various file manipulations are supported. See below for a full list of the subcommands available and a brief description of their purpose. Most of the individual subcommands will take either a single file or a pair of files as input. If no input file is specified, fqtools will attempt to read data from&nbsp;</span><code>stdin</code><span>. In this case, it is advisabe to specify the format of the data provided. For subcommands that generate FASTQ data, either a single file or a pair of files will be generated. If no&nbsp;</span><code>-o</code><span>&nbsp;argument is provided, single files will be writted to&nbsp;</span><code>stdout</code><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/alastair-droop/fqtools" rel="nofollow">https://github.com/alastair-droop/fqtools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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