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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38505?offset=280</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</guid>
	<pubDate>Mon, 17 Feb 2020 05:38:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny</link>
	<title><![CDATA[Chromonomer: a tool set for repairing and enhancing assembled genomes through integration of genetic maps and conserved synteny]]></title>
	<description><![CDATA[<p>Chromonomer is a program designed to integrate a genome assembly with a genetic map. Chromonomer tries very hard to identify and remove markers that are out of order in the genetic map, when considered against their local assembly order; and to identify scaffolds that have been incorrectly assembled according to the genetic map, and split those scaffolds.</p><p>Address of the bookmark: <a href="http://catchenlab.life.illinois.edu/chromonomer/" rel="nofollow">http://catchenlab.life.illinois.edu/chromonomer/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</guid>
	<pubDate>Thu, 19 Nov 2020 07:04:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42325/published-a-dataset-of-363-genomes-from-approximately-92-percent-of-bird-families</link>
	<title><![CDATA[Published a dataset of 363 genomes from approximately 92 percent of bird families]]></title>
	<description><![CDATA[<div>A research team published a dataset of 363 genomes from approximately 92 percent of bird families and showed the significance of sampling dense organisms for biodiversity research. The study was jointly conducted by Chinese and international institutions and museums and was led by researchers from the Kunming Institute of Zoology (KIZ) of the Chinese Academy of Sciences (CAS). Total of 267 were newly published among the 363 sequenced genomes.&nbsp;They were mainly taken from samples of avian tissue kept in museums around the world, enabling researchers to sequence rare and endangered birds' genomes.</div><div>&nbsp;</div><div>Its descendants have adapted to a wide variety of ecological niches since the first bird formed more than 150 million years ago, giving rise to small, hovering hummingbirds, plunge-diving pelicans and showy paradise birds. More than 10,000 bird species live on the planet today - and now scientists are well on their way to capturing a full genetic image of that diversity.</div><div>&nbsp;</div><div>B10K is expanding its efforts to encompass the next stage of avian classification with 363 genomes complete. The team will sequence thousands of extra genomes in this process, attempting to represent each of the approximately 2,300 bird genera.</div><div>&nbsp;</div><div><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-020-2873-9/MediaObjects/41586_2020_2873_Fig1_HTML.png?as=webp" alt="image" style="border: 0px;"></div><div>&nbsp;</div><div>The genomic resource is expected to provide new insights on evolutionary processes in cross-species comparative studies and assist in efforts to protect species, according to the research findings reported as a cover story in the journal Nature.</div><div>&nbsp;</div><div>Ref at&nbsp;Dense sampling of bird diversity increases power of comparative genomics&nbsp;https://www.nature.com/articles/s41586-020-2873-9</div>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</guid>
	<pubDate>Mon, 06 May 2024 06:21:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44525/synorth-exploring-the-evolution-of-synteny-and-long-range-regulatory-interactions-in-vertebrate-genomes</link>
	<title><![CDATA[Synorth: exploring the evolution of synteny and long-range regulatory interactions in vertebrate genomes]]></title>
	<description><![CDATA[<p><span>Genomic regulatory blocks are chromosomal regions spanned by long clusters of highly conserved noncoding elements devoted to long-range regulation of developmental genes, often immobilizing other, unrelated genes into long-lasting syntenic arrangements. Synorth&nbsp;</span><a href="http://synorth.genereg.net/" target="_blank">http://synorth.genereg.net/</a><span>&nbsp;is a web resource for exploring and categorizing the syntenic relationships in genomic regulatory blocks across multiple genomes, tracing their evolutionary fate after teleost whole genome duplication at the level of genomic regulatory block loci, individual genes, and their phylogenetic context.</span></p>
<p><span>More at&nbsp;https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745767/</span></p><p>Address of the bookmark: <a href="http://synorth.genereg.net/" rel="nofollow">http://synorth.genereg.net/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</guid>
	<pubDate>Wed, 06 Dec 2017 01:05:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</link>
	<title><![CDATA[HiC-Pro: an optimized and flexible pipeline for Hi-C data processing]]></title>
	<description><![CDATA[<p><span>HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.</span></p>
<p>&nbsp;</p>
<p>http://nservant.github.io/HiC-Pro/</p><p>Address of the bookmark: <a href="http://nservant.github.io/HiC-Pro/" rel="nofollow">http://nservant.github.io/HiC-Pro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</guid>
	<pubDate>Fri, 04 Sep 2020 20:41:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/42188/tools-and-method-for-haplotype-phasing</link>
	<title><![CDATA[Tools and Method for Haplotype phasing !]]></title>
	<description><![CDATA[<div>Huge amounts of genotype data are being produced with recent technological advances, both from increasingly&nbsp; comprehensive and inexpensive genome-wide SNP microarrays and from ever more accessible whole-genome and whole-exome sequencing methods. The vast amount of knowledge contained in these results, however, is best&nbsp; exploited through phased haplotypes, which classify the alleles co-located on the same chromosome. Since sequence and SNP array data normally take the form of unphased genotypes, one does not specifically observe which of the two parental chromosomes, or haplotypes, falls on a specific allele. Fortunately, new advances in both computational and laboratory methods promise improved determination of haplotype phase. Following are useful tools :</div><div>&nbsp;</div><p><strong>Arlequin:</strong>&nbsp;<a href="http://cmpg.unibe.ch/software/arlequin3/" target="_blank">http://cmpg.unibe.ch/software/arlequin3/</a></p><p><strong>BEAGLE:</strong>&nbsp;<a href="http://faculty.washington.edu/browning/beagle/beagle.html" target="_blank">http://faculty.washington.edu/browning/beagle/beagle.html</a></p><p><strong>fastPHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>GENEHUNTER:</strong>&nbsp;<a href="http://linkage.rockefeller.edu/soft/gh/" target="_blank">http://linkage.rockefeller.edu/soft/gh/</a></p><p><strong>The Genome Analysis Toolkit:</strong></p><p><a href="http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit</a></p><p><strong>IMPUTE2:</strong>&nbsp;<a href="https://mathgen.stats.ox.ac.uk/impute/impute_v2.html" target="_blank">https://mathgen.stats.ox.ac.uk/impute/impute_v2.html</a></p><p><strong>MACH:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/MACH/" target="_blank">http://www.sph.umich.edu/csg/abecasis/MACH/</a></p><p><strong>MERLIN:</strong>&nbsp;<a href="http://www.sph.umich.edu/csg/abecasis/Merlin/" target="_blank">http://www.sph.umich.edu/csg/abecasis/Merlin/</a></p><p><strong>PHASE:</strong>&nbsp;<a href="http://stephenslab.uchicago.edu/software.html" target="_blank">http://stephenslab.uchicago.edu/software.html</a></p><p><strong>PL-EM:</strong>&nbsp;<a href="http://www.people.fas.harvard.edu/~junliu/plem/" target="_blank">http://www.people.fas.harvard.edu/~junliu/plem/</a></p><p><strong>&ldquo;Read-backed phasing&rdquo; algorithm</strong>:&nbsp;<a href="http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm" target="_blank">http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm</a></p><p><strong>SHAPE-IT:</strong>&nbsp;<a href="http://www.griv.org/shapeit/" target="_blank">http://www.griv.org/shapeit/</a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32481/sspace</guid>
	<pubDate>Fri, 05 May 2017 05:42:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32481/sspace</link>
	<title><![CDATA[SSPACE]]></title>
	<description><![CDATA[<p>SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" rel="nofollow">https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35918/scubat-scaffolding-contigs-using-blat-and-transcripts</guid>
	<pubDate>Tue, 13 Mar 2018 06:52:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35918/scubat-scaffolding-contigs-using-blat-and-transcripts</link>
	<title><![CDATA[SCUBAT: Scaffolding Contigs Using Blat And Transcripts]]></title>
	<description><![CDATA[<p><span>SCUBAT (Scaffolding Contigs Using BLAT And Transcripts) uses any set of transcripts to identify cases where a transcript is split over multiple genome fragments and attempts to use this information to scaffold the genome.</span></p><p>Address of the bookmark: <a href="https://github.com/elswob/SCUBAT" rel="nofollow">https://github.com/elswob/SCUBAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</guid>
	<pubDate>Tue, 06 Mar 2018 16:39:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35885/multi-car-a-tool-of-contig-scaffolding-using-multiple-references</link>
	<title><![CDATA[Multi-CAR: a tool of contig scaffolding using multiple references]]></title>
	<description><![CDATA[<p><span>we design a simple heuristic method to further revise our single reference-based scaffolding tool CAR into a new one called Multi-CAR such that it can utilize multiple complete genomes of related organisms as references to more accurately order and orient the contigs of a draft genome. In practical usage, our Multi-CAR does not require prior knowledge concerning phylogenetic relationships among the draft and reference genomes and libraries of paired-end reads. To validate Multi-CAR, we have tested it on a real dataset composed of several prokaryotic genomes and also compared its accuracy performance with other multiple reference-based scaffolding tools Ragout and MeDuSa.&nbsp;</span></p><p>Address of the bookmark: <a href="http://genome.cs.nthu.edu.tw/Multi-CAR/" rel="nofollow">http://genome.cs.nthu.edu.tw/Multi-CAR/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</guid>
	<pubDate>Sat, 04 Jan 2020 01:08:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40510/reps-repeat-masked-phrap-with-scaffolding-a-wgs-sequence-assembler</link>
	<title><![CDATA[RePS: Repeat-masked Phrap with scaffolding, a WGS sequence assembler]]></title>
	<description><![CDATA[<p>RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering</p>
<p><img src="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/bin/45793-17f1_F4TT.jpg" alt="image" style="border: 0px;"></p>
<p>More at</p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/</a></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz" rel="nofollow">ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34398/ont-assembly-and-illumina-polishing-pipeline</guid>
	<pubDate>Thu, 23 Nov 2017 10:13:42 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34398/ont-assembly-and-illumina-polishing-pipeline</link>
	<title><![CDATA[ONT assembly and Illumina polishing pipeline]]></title>
	<description><![CDATA[<p>This pipeline performs the following steps:</p>
<ul>
<li>Assembly of nanopore reads using&nbsp;<a href="http://canu.readthedocs.io/">Canu</a>.</li>
<li>Polish canu contigs using&nbsp;<a href="https://github.com/isovic/racon">racon</a>&nbsp;(<em>optional</em>).</li>
<li>Map a paired-end Illumina dataset onto the contigs obtained in the previous steps using&nbsp;<a href="http://bio-bwa.sourceforge.net/">BWA</a>&nbsp;mem.</li>
<li>Perform correction of contigs using&nbsp;<a href="https://github.com/broadinstitute/pilon/wiki">pilon</a>&nbsp;and the Illumina dataset.</li>
</ul><p>Address of the bookmark: <a href="https://github.com/nanoporetech/ont-assembly-polish" rel="nofollow">https://github.com/nanoporetech/ont-assembly-polish</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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