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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37239?offset=340</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26322/liftover</guid>
	<pubDate>Mon, 08 Feb 2016 15:45:03 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26322/liftover</link>
	<title><![CDATA[liftover]]></title>
	<description><![CDATA[<p><span>Convenient conversions between genome assemblie.&nbsp;The liftover package makes it easy to remap genomic coordinates to a different genome assembly. </span></p>
<p><span>More at https://github.com/aaronwolen/liftover<br></span></p>
<p><span>https://www.bioconductor.org/help/workflows/liftOver/</span></p><p>Address of the bookmark: <a href="https://github.com/aaronwolen/liftover" rel="nofollow">https://github.com/aaronwolen/liftover</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27113/picard</guid>
	<pubDate>Fri, 29 Apr 2016 08:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27113/picard</link>
	<title><![CDATA[Picard]]></title>
	<description><![CDATA[<p>Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the <a href="http://samtools.github.io/hts-specs/">Hts-specs</a> repository. See especially the <a href="http://samtools.github.io/hts-specs/SAMv1.pdf">SAM specification</a> and the <a href="http://samtools.github.io/hts-specs/VCFv4.3.pdf">VCF specification</a>.</p>
<p>Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on <a href="https://github.com/broadinstitute/picard">GitHub</a>.</p>
<p>The Picard toolkit is open-source under the <a href="https://tldrlegal.com/license/mit-license">MIT license</a> and free for all uses.</p>
<p>Enjoy!</p><p>Address of the bookmark: <a href="http://broadinstitute.github.io/picard/" rel="nofollow">http://broadinstitute.github.io/picard/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26911/raca-reference-assisted-chromosome-assembly</guid>
	<pubDate>Wed, 06 Apr 2016 09:29:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26911/raca-reference-assisted-chromosome-assembly</link>
	<title><![CDATA[RACA: Reference-Assisted Chromosome Assembly]]></title>
	<description><![CDATA[<p>Rreference-Assisted Chromosome Assembly (RACA), an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.</p>
<p>http://www.ncbi.nlm.nih.gov/pubmed/23307812</p>
<p>http://bioen-compbio.bioen.illinois.edu/RACA/</p><p>Address of the bookmark: <a href="http://bioen-compbio.bioen.illinois.edu/RACA/" rel="nofollow">http://bioen-compbio.bioen.illinois.edu/RACA/</a></p>]]></description>
	<dc:creator>Priya Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26999/discovar</guid>
	<pubDate>Mon, 18 Apr 2016 11:59:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26999/discovar</link>
	<title><![CDATA[DISCOVAR]]></title>
	<description><![CDATA[<p><strong>DISCOVAR</strong> is a new variant caller and <strong>DISCOVAR <em>de novo</em></strong> a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer &mdash; produced on MiSeq or HiSeq 2500 &mdash; and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.</p>
<p><strong>DISCOVAR</strong> can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.</p>
<p><strong>DISCOVAR <em>de novo</em></strong> can generate <em>de novo</em> assemblies for both large and small genomes. It currently does not call variants.</p>
<p>More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/discovar/blog/" rel="nofollow">https://www.broadinstitute.org/software/discovar/blog/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</guid>
	<pubDate>Tue, 26 Apr 2016 12:18:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences</link>
	<title><![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]></title>
	<description><![CDATA[<p><strong>Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements</strong><span>. The detection is based on&nbsp;</span><strong>conditional exclusive compression</strong><span>, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a&nbsp;</span><strong>SVG image</strong><span>, with an&nbsp;</span><strong>ideogram</strong><span>output architecture, where the patterns are represented with several&nbsp;</span><strong>HSV values</strong><span>&nbsp;(only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to&nbsp;</span><strong>know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes</strong><span>.</span></p><p>Address of the bookmark: <a href="http://bioinformatics.ua.pt/software/smash/" rel="nofollow">http://bioinformatics.ua.pt/software/smash/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27328/platanus</guid>
	<pubDate>Fri, 13 May 2016 05:12:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27328/platanus</link>
	<title><![CDATA[Platanus]]></title>
	<description><![CDATA[<p>Platanus is a novel <em>de novo</em> sequence assembler that can reconstruct genomic sequences of<br> highly heterozygous diploids from massively parallel shotgun sequencing data.</p>
<p>The latest version is <a href="http://platanus.bio.titech.ac.jp/platanus/?page_id=14">1.2.4</a>.</p>
<p>To cite Platanus, please use the following:</p>
<p>Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, Yabana M, Harada M, Nagayasu E, Maruyama H, Kohara Y, Fujiyama A, Hayashi T, Itoh T, &ldquo;Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads&rdquo;.&nbsp;Genome Res. 2014 Aug;24(8):1384-95. doi: 10.1101/gr.170720.113. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/24755901">abstract</a> |<a href="http://genome.cshlp.org/content/24/8/1384.long"> full text</a>]</p><p>Address of the bookmark: <a href="http://platanus.bio.titech.ac.jp/" rel="nofollow">http://platanus.bio.titech.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</guid>
	<pubDate>Tue, 14 Jun 2016 06:18:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27818/gaemr</link>
	<title><![CDATA[GAEMR]]></title>
	<description><![CDATA[<p>The&nbsp;<span>G</span>enome&nbsp;<span>A</span>ssembly&nbsp;<span>E</span>valuation&nbsp;<span>M</span>etrics and&nbsp;<span>R</span>eporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR&rsquo;s analysis pipeline, hence enabling the generation of standard reports.</p>
<p>GAEMR&rsquo;s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.&nbsp;</p><p>Address of the bookmark: <a href="https://www.broadinstitute.org/software/gaemr/" rel="nofollow">https://www.broadinstitute.org/software/gaemr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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