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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31351?offset=500</link>
	<atom:link href="https://bioinformaticsonline.com/related/31351?offset=500" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36985/swalo-scaffolding-with-assembly-likelihood-optimization</guid>
	<pubDate>Wed, 20 Jun 2018 02:45:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36985/swalo-scaffolding-with-assembly-likelihood-optimization</link>
	<title><![CDATA[SWALO: Scaffolding with assembly likelihood optimization]]></title>
	<description><![CDATA[SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.

Please email your questions, comments, suggestions, and bug reports to atif.bd@gmail.com.<p>Address of the bookmark: <a href="https://atifrahman.github.io/SWALO/" rel="nofollow">https://atifrahman.github.io/SWALO/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</guid>
	<pubDate>Sat, 25 Feb 2017 17:52:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</link>
	<title><![CDATA[BioDownloader]]></title>
	<description><![CDATA[<p><strong><em>BioDownloader</em></strong> is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:</p>
<ul>
<li>optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).</li>
<li>allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)</li>
<li>has a built-in repository containing the settings for the most common bioinformatics download needs</li>
<li>built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)</li>
<li>capable of performing multiple download or update tasks simultaneously</li>
</ul>
<p>BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.</p>
<p>http://dunbrack.fccc.edu/BioDownloader/</p><p>Address of the bookmark: <a href="http://dunbrack.fccc.edu/BioDownloader/" rel="nofollow">http://dunbrack.fccc.edu/BioDownloader/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</guid>
	<pubDate>Fri, 17 Feb 2017 16:13:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</link>
	<title><![CDATA[DAGchainer: Computing Chains of Syntenic Genes in Complete Genomes]]></title>
	<description><![CDATA[<p>The DAGchainer software computes chains of syntenic genes found within complete genome sequences. As input, DAGchainer accepts a list of gene pairs with sequence homology along with their genome coordinates. Using a scoring function which accounts for the distance between neighboring genes on each DNA molecule and the BLAST E-value score between homologs, maximally scoring chains of ordered gene pairs are computed and reported. This algorithm can be used to mine large evolutionary conserved regions of genomes between two organisms. Alternatively, by examining colinear sets of homologous genes found within a single genome, segmental genome duplications can be revealed.</p>
<p>This software distribution includes both the DAGchainer utility and a Java-based graphical interface that allows the inputs and outputs to be navigated and interrogated dynamically.</p><p>Address of the bookmark: <a href="http://dagchainer.sourceforge.net/" rel="nofollow">http://dagchainer.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</guid>
	<pubDate>Wed, 01 Mar 2017 08:32:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31205/yasra-reference-based-assembler</link>
	<title><![CDATA[YASRA: Reference based assembler]]></title>
	<description><![CDATA[<p>YASRA (Yet Another Short Read Assembler) performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced. Mapping reads to reference genomes makes use of LASTZ (Harris et al), a pairwise sequence aligner compatible with BLASTZ. Special scoring sets were derived to improve the performance, both in runtime and quality for 454 and Illumina sequence reads.</p>
<p>YASRA uses LASTZ (<a href="http://bx.psu.edu/miller_lab">http://bx.psu.edu/miller_lab</a> for released version and <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a> for newer version) for aligning the sequences to the reference genome. Please install LASTZ (the newest version on <a href="http://www.bx.psu.edu/%7Ersharris/lastz/newer">http://www.bx.psu.edu/~rsharris/lastz/newer</a>) and add the LASTZ binary in your executable/binary search path before installing YASRA.</p><p>Address of the bookmark: <a href="https://github.com/aakrosh/YASRA" rel="nofollow">https://github.com/aakrosh/YASRA</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31564/htslib</guid>
	<pubDate>Wed, 15 Mar 2017 11:38:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31564/htslib</link>
	<title><![CDATA[HTSlib]]></title>
	<description><![CDATA[<p>Samtools is a suite of programs for interacting with high-throughput sequencing data. It consists of three separate repositories:</p>
<dl><dt>Samtools</dt><dd>Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format</dd><dt>BCFtools</dt><dd>Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants</dd><dt>HTSlib</dt><dd>A C library for reading/writing high-throughput sequencing data</dd></dl>
<p>Samtools and BCFtools both use HTSlib internally, but these source packages contain their own copies of htslib so they can be built independently.</p><p>Address of the bookmark: <a href="http://www.htslib.org/" rel="nofollow">http://www.htslib.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31976/snpgenie</guid>
	<pubDate>Thu, 30 Mar 2017 17:38:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31976/snpgenie</link>
	<title><![CDATA[SNPGenie]]></title>
	<description><![CDATA[<p>SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a single population, with variants called relative to a single reference sequence (one sequence in one FASTA file). Just run the main script, <strong>snpgenie.pl</strong>, in a directory containing the necessary <a href="https://github.com/hugheslab/snpgenie#snpgenie-input">input files</a>, and we take care of the rest! For the earlier version, see <a href="http://ww2.biol.sc.edu/~austin/">Hughes Lab Bioinformatics Resource</a>.</p><p>Address of the bookmark: <a href="https://github.com/hugheslab/snpgenie" rel="nofollow">https://github.com/hugheslab/snpgenie</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</guid>
	<pubDate>Mon, 10 Apr 2017 04:45:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</link>
	<title><![CDATA[WGS Celera Assembler version 8.3rc2]]></title>
	<description><![CDATA[<p>These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.<br><br>This distribution package provides a stable, tested, documented version of the software.&nbsp; The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.<br><br>The source code package includes full source code (revision 4627), Makefiles, and scripts.&nbsp; A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.&nbsp; This distribution includes [http://samtools.sourceforge.net/ SAMtools], [http://www.cbcb.umd.edu/software/jellyfish/ Jellyfish 2.0], [https://github.com/pbjd/pbutgcns PBUTGCNS], [https://github.com/PacificBiosciences/pbdagcon PBDAGCON], [https://github.com/PacificBiosciences/BLASR BLASR], and parts of the [https://github.com/PacificBiosciences/FALCON/tree/v0.1.3 Falcon assembler].<br><br>Full documentation can be found online at http://wgs-assembler.sourceforge.net/.</p>
<p>Interesting scripts within it</p>
<p>urbe@urbo214b[bin] ls&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; []<br>-rwxrwxr-x 1 urbe urbe&nbsp; 11K Apr 10 11:41 addCNSToStore<br>-rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs<br>-rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest<br>-rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds<br>-rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta<br>-rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics<br>-rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl<br>-rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr<br>-rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart<br>-rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus<br>-rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness<br>-rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap<br>-rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs<br>-rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:41 ca2ace.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 12K Apr 10 11:41 caqc_help.ini<br>-rwxrwxr-x 1 urbe urbe&nbsp; 61K Apr 10 11:41 caqc.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 23K Apr 10 11:41 cat-corrects<br>-rwxrwxr-x 1 urbe urbe&nbsp; 24K Apr 10 11:41 cat-erates<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump<br>-rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera<br>-rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply<br>-rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise<br>-rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 convertOverlap<br>-rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 20K Apr 10 11:41 convertToPBCNS<br>-rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags<br>-rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps<br>-rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio<br>-rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns<br>-rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate<br>-rwxrwxr-x 1 urbe urbe&nbsp; 37K Apr 10 11:41 demotePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons<br>-rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate<br>-rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition<br>-rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages<br>-rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze<br>-rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample<br>-rwxrwxr-x 1 urbe urbe&nbsp; 62K Apr 10 11:40 fastqSimulate<br>-rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort<br>-rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA<br>-rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap<br>-rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim<br>-rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth<br>-rwxrwxr-x 1 urbe urbe&nbsp; 29K Apr 10 11:41 fragsInVars<br>-rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones<br>-rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench<br>-rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ<br>-rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling<br>-rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM<br>-rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim<br>-rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish<br>-rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique<br>-rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique<br>-rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy<br>-rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl<br>-rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim<br>-rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply<br>-rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl<br>-rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds<br>-rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout<br>-rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore<br>-rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer<br>-rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe&nbsp; 33K Apr 10 11:41 overlapStoreIndexer<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 overlapStoreSorter<br>-rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry<br>lrwxrwxrwx 1 urbe urbe&nbsp;&nbsp;&nbsp; 4 Apr 10 11:41 pacBioToCA -&gt; PBcR<br>-rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR<br>-rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap<br>-rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq<br>-rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache<br>-rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 88K Apr 10 11:41 runCA-dedupe<br>-rwxrwxr-x 1 urbe urbe&nbsp; 14K Apr 10 11:41 runCA-overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 13K Apr 10 11:40 show-corrects<br>-rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator<br>drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR<br>-rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracearchiveToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracedb-to-frg.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 44K Apr 10 11:41 trimFastqByQVWindow<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:40 uidclient<br>-rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v8-to-v9<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v9-to-v10<br>-rwxrwxr-x 1 urbe urbe&nbsp; 854 Apr 10 11:41 utg2fasta<br>-rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns<br>-rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix<br><br><br></p><p>Address of the bookmark: <a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page" rel="nofollow">http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</guid>
	<pubDate>Mon, 04 Feb 2019 04:53:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38892/wtdbg2-a-fuzzy-bruijn-graph-approach-to-long-noisy-reads-assembly</link>
	<title><![CDATA[wtdbg2: A fuzzy Bruijn graph approach to long noisy reads assembly]]></title>
	<description><![CDATA[<p><span>Wtdbg2 is a&nbsp;</span><em>de novo</em><span>&nbsp;sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output.&nbsp;</span></p>
<pre>./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa</pre><p>Address of the bookmark: <a href="https://github.com/ruanjue/wtdbg2" rel="nofollow">https://github.com/ruanjue/wtdbg2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization</guid>
	<pubDate>Wed, 19 Apr 2017 04:06:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32187/chromhmm-chromatin-state-discovery-and-characterization</link>
	<title><![CDATA[ChromHMM: Chromatin state discovery and characterization]]></title>
	<description><![CDATA[<p><span>ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser.&nbsp;</span><br><br></p>
<ul>
<li><a href="http://compbio.mit.edu/ChromHMM/ChromHMM.zip">ChromHMM software v1.12</a>&nbsp;(<a href="http://compbio.mit.edu/ChromHMM/versionlog.txt">version log</a>)</li>
<li><a href="http://compbio.mit.edu/ChromHMM/ChromHMM_manual.pdf">ChromHMM manual</a></li>
</ul><p>Address of the bookmark: <a href="http://compbio.mit.edu/ChromHMM/" rel="nofollow">http://compbio.mit.edu/ChromHMM/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<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>
</item>

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