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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30140?offset=1170</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</guid>
	<pubDate>Mon, 13 Feb 2017 08:40:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter</link>
	<title><![CDATA[fineSTRUCTURE v2 &amp; GLOBETROTTER]]></title>
	<description><![CDATA[<p>Software available at this site</p>
<div>
<ul>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure_info.html">FineSTRUCTURE version 2</a>, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructureR.html">FineSTRUCTURE R scripts</a>, a facility for exploring the results when the GUI is unavailable.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/globetrotter.html">GLOBETROTTER</a>, the admixture dating method based on ChromoPainter. Download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/admixture.html">AdmixturePainting</a>, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.</li>
<li><a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/radpainter.html">RADpainter</a>, finestructure and ChromoPainter for RAD tag data used for non-model organisms.</li>
<li>Scripts to perform many types of conversion. Included in the main software download from the <a href="https://people.maths.bris.ac.uk/%7Emadjl/finestructure/finestructure.html">Downloads</a> page.</li>
</ul>
What this page is This page provides information about and downloads for <strong>methodology for Chromosome Painting</strong>. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!<br> About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.</div><p>Address of the bookmark: <a href="http://paintmychromosomes.com/" rel="nofollow">http://paintmychromosomes.com/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36867/cerulean-a-hybrid-assembly-using-high-throughput-short-and-long-reads</guid>
	<pubDate>Tue, 05 Jun 2018 10:10:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36867/cerulean-a-hybrid-assembly-using-high-throughput-short-and-long-reads</link>
	<title><![CDATA[Cerulean: A hybrid assembly using high throughput short and long reads]]></title>
	<description><![CDATA[Cerulean extends contigs assembled using short read datasets like Illumina paired-end reads using long reads like PacBio RS long reads.

Cerulean v0.1 has been implemented with bacterial genomes in mind.

The method is fully described in Deshpande, V., Fung, E. D., Pham, S., &amp; Bafna, V. (2013). Cerulean: A hybrid assembly using high throughput short and long reads. arXiv preprint arXiv:1307.7933.
http://arxiv.org/abs/1307.7933<p>Address of the bookmark: <a href="https://sourceforge.net/projects/ceruleanassembler/" rel="nofollow">https://sourceforge.net/projects/ceruleanassembler/</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</guid>
	<pubDate>Tue, 03 Jul 2018 04:14:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37223/chopstitch-exon-annotation-and-splice-graph-construction-using-transcriptome-assembly-and-whole-genome-sequencing-data</link>
	<title><![CDATA[ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data]]></title>
	<description><![CDATA[ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.<p>Address of the bookmark: <a href="https://github.com/bcgsc/ChopStitch" rel="nofollow">https://github.com/bcgsc/ChopStitch</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</guid>
	<pubDate>Mon, 20 Aug 2018 04:08:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37554/finishersca-repeat-aware-tool-for-upgrading-de-novo-assembly-using-long-reads</link>
	<title><![CDATA[FinisherSC:a repeat-aware tool for upgrading de novo assembly using long reads]]></title>
	<description><![CDATA[<p><br>Here is the command to run the tool:</p>
<pre><code>python finisherSC.py destinedFolder mummerPath
</code></pre>
<p>If you are running on server computer and would like to use multiple threads, then the following commands can generate 20 threads to run FinisherSC.</p>
<pre><code>python finisherSC.py -par 20 destinedFolder mummerPath
</code></pre>
<p>Sometimes, if the names of raw reads and contigs consists of special characters/formats, FinisherSC/MUMmer may not parse them correctly. In that case, you want to have a quick renaming of the names of contigs/reads in contigs.fasta or raw_reads.fasta using the following command.</p>
<pre><code>    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' raw_reads.fasta &gt; newRaw_reads.fasta
    cp newRaw_reads.fasta raw_reads.fasta
    perl -pe 's/&gt;[^\$]*$/"&gt;Seg" . ++$n ."\n"/ge' contigs.fasta &gt; newContigs.fasta
    cp newContigs.fasta contigs.fasta</code></pre><p>Address of the bookmark: <a href="https://github.com/kakitone/finishingTool" rel="nofollow">https://github.com/kakitone/finishingTool</a></p>]]></description>
	<dc:creator>Jit</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/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</guid>
	<pubDate>Thu, 14 May 2020 15:09:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</link>
	<title><![CDATA[LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly]]></title>
	<description><![CDATA[<p>LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.</p><p>Address of the bookmark: <a href="https://github.com/CAFS-bioinformatics/LR_Gapcloser" rel="nofollow">https://github.com/CAFS-bioinformatics/LR_Gapcloser</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</guid>
	<pubDate>Sun, 26 Mar 2017 15:41:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31881/gbtools-interactive-visualization-of-metagenome-bins-in-r</link>
	<title><![CDATA[gbtools: Interactive Visualization of Metagenome Bins in R]]></title>
	<description><![CDATA[<p><span>We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other.&nbsp;</span></p>
<p><span>Tool at&nbsp;https://github.com/kbseah/genome-bin-tools</span></p><p>Address of the bookmark: <a href="http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full" rel="nofollow">http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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