<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36865?offset=50</link>
	<atom:link href="https://bioinformaticsonline.com/related/36865?offset=50" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36893/beap-blast-extension-and-assembly-program</guid>
	<pubDate>Mon, 11 Jun 2018 04:52:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36893/beap-blast-extension-and-assembly-program</link>
	<title><![CDATA[BEAP: Blast Extension and Assembly Program]]></title>
	<description><![CDATA[The Blast Extension and Assembly Program (BEAP) is a computer program that uses a short starting DNA fragment, often a EST or partial gene segment, as "primer", to recursively blast nucleotide databases in an attempt to obtain all sequences that overlaps, directly or indirectly, with the "primer" therefore help to "extend" the length of the original sequence for constructing a "full length" sequence for functional analysis, or at least to obtain neighboring regions of the segment for SNP discovery and linkage disequilibrium analysis. The confidence of assembling the resulting sequences is achieved by using a known genome, such as human genome, as a reference.
 
https://www.animalgenome.org/tools/beap/<p>Address of the bookmark: <a href="https://www.animalgenome.org/tools/beap/" rel="nofollow">https://www.animalgenome.org/tools/beap/</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43770/chromeister-an-ultra-fast-heuristic-approach-to-detect-conserved-signals-in-extremely-large-pairwise-genome-comparisons</guid>
	<pubDate>Thu, 03 Feb 2022 04:01:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43770/chromeister-an-ultra-fast-heuristic-approach-to-detect-conserved-signals-in-extremely-large-pairwise-genome-comparisons</link>
	<title><![CDATA[chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.]]></title>
	<description><![CDATA[<p>chromeister: An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons.</p>
<p dir="auto">USAGE:</p>
<ul dir="auto">
<li>-query: sequence A in fasta format</li>
<li>-db: sequence B in fasta format</li>
<li>-out: output matrix</li>
<li>-kmer Integer: k&gt;1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria</li>
<li>-diffuse Integer: z&gt;0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1</li>
<li>-dimension Size of the output matrix and plot. Integer: d&gt;0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended</li>
</ul><p>Address of the bookmark: <a href="https://github.com/estebanpw/chromeister" rel="nofollow">https://github.com/estebanpw/chromeister</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</guid>
	<pubDate>Tue, 16 Aug 2016 08:34:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28809/kissplice</link>
	<title><![CDATA[KisSplice]]></title>
	<description><![CDATA[<p>KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.</p>
<p>KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.</p>
<p>KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.</p><p>Address of the bookmark: <a href="http://kissplice.prabi.fr/" rel="nofollow">http://kissplice.prabi.fr/</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/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</guid>
	<pubDate>Mon, 10 Jul 2017 10:09:27 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33859/disco-multi-threaded-and-multiprocess-distributed-memory-overlap-layout-consensus-olc-metagenome-assembler</link>
	<title><![CDATA[DISCO : multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler]]></title>
	<description><![CDATA[<p><span>DISCO is a multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler. Disco was developed as a&nbsp;scalable assembler to assemble large metagenomes from billions of Illumina sequencing reads of complex microbial communities. Disco was parallelized for computer clusters in a hybrid architecture that integrated shared-memory multi-threading, point-to-point message passing, and remote direct memory access. The assembly and scaffolding were performed using an iterative overlap graph approach.</span></p><p>Address of the bookmark: <a href="http://disco.omicsbio.org/" rel="nofollow">http://disco.omicsbio.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40895/tadpole-an-assembler-error-corrector-and-read-extender</guid>
	<pubDate>Tue, 04 Feb 2020 23:35:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40895/tadpole-an-assembler-error-corrector-and-read-extender</link>
	<title><![CDATA[Tadpole: an assembler, error-corrector, and read-extender]]></title>
	<description><![CDATA[<p><span>Tadpole is a kmer-based assembler, with additional capabilities of error-correcting and extending reads. It does not do any complicated graph analysis or scaffolding, and therefore, is not particularly good for diploid organisms.&nbsp;</span><span>Tadpole is very conservative and optimized for correctness rather than length; which is to say, it stops at every branch, and condenses every repeat. Also, it does not currently do scaffolding.</span></p>
<p>&nbsp;</p>
<p><span><span>To error-correct reads:</span><br><strong>tadpole.sh in=reads.fq out=corrected.fq mode=correct</strong><br><br><span>To extend reads by 50bp in each direction:</span><br><strong>tadpole.sh in=reads.fq out=extended.fq mode=extend el=50 er=50</strong><br><br><span>To error-correct and extend at the same time, using a kmer length of 62:</span><br><strong>tadpole.sh in=reads.fq out=extended.fq mode=extend el=50 er=50 k=62 ecc=t</strong></span></p>
<p>&nbsp;</p>
<p>More at&nbsp;<a href="http://seqanswers.com/forums/showthread.php?t=61445">http://seqanswers.com/forums/showthread.php?t=61445</a></p><p>Address of the bookmark: <a href="https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/tadpole-guide/" rel="nofollow">https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/tadpole-guide/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</guid>
	<pubDate>Wed, 21 Aug 2013 07:56:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/2726/comparison-of-short-read-de-novo-alignment-algorithms</link>
	<title><![CDATA[Comparison of Short Read De Novo Alignment Algorithms]]></title>
	<description><![CDATA[<p>Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references.</p>
<p>Title:&nbsp;<strong>Comparison of Short Read De Novo Alignment Algorithms&nbsp;</strong></p>
<p>Author<strong>: Nikhil Gopal</strong></p><p>Address of the bookmark: <a href="http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf" rel="nofollow">http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</guid>
	<pubDate>Sat, 25 Nov 2017 08:57:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34413/coursera-genome-assembly-tutorial</link>
	<title><![CDATA[coursera genome assembly tutorial]]></title>
	<description><![CDATA[<p><span>Solutions to Coursera Genome Sequencing (Bioinformatics II)</span></p><p>Address of the bookmark: <a href="https://github.com/iansealy/coursera-assembly" rel="nofollow">https://github.com/iansealy/coursera-assembly</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</guid>
	<pubDate>Thu, 25 Jan 2018 05:47:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35345/rgfa-powerful-and-convenient-handling-of-assembly-graphs</link>
	<title><![CDATA[RGFA: powerful and convenient handling of assembly graphs]]></title>
	<description><![CDATA[<p><span>RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.</span></p>
<p><span>https://github.com/ggonnella/rgfa</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

</channel>
</rss>