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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41033?offset=130</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</guid>
	<pubDate>Tue, 12 Dec 2017 17:30:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34620/mash-fast-genome-and-metagenome-distance-estimation-using-minhash</link>
	<title><![CDATA[Mash: fast genome and metagenome distance estimation using MinHash]]></title>
	<description><![CDATA[<p>Mash is normally distributed as a dependency-free binary for Linux or OSX (see&nbsp;<a href="https://github.com/marbl/Mash/releases">https://github.com/marbl/Mash/releases</a>). This source distribution is intended for other operating systems or for development. Mash requires c++11 to build, which is available in and GCC &gt;= 4.8 and OSX &gt;= 10.7.</p>
<p>See&nbsp;<a href="http://mash.readthedocs.org/">http://mash.readthedocs.org</a>&nbsp;for more information.</p><p>Address of the bookmark: <a href="https://github.com/marbl/Mash/releases" rel="nofollow">https://github.com/marbl/Mash/releases</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</guid>
	<pubDate>Tue, 15 May 2018 04:44:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36618/lamsa-fast-split-read-alignment-with-long-approximate-matches</link>
	<title><![CDATA[LAMSA: fast split read alignment with long approximate matches]]></title>
	<description><![CDATA[LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs).

LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants.

We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs.

LAMSA is open source and free for non-commercial use.

LAMSA is mainly designed by Bo Liu &amp; Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.<p>Address of the bookmark: <a href="https://github.com/hitbc/LAMSA" rel="nofollow">https://github.com/hitbc/LAMSA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</guid>
	<pubDate>Wed, 29 Aug 2018 09:20:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing</link>
	<title><![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]></title>
	<description><![CDATA[<p><em>indexcov</em><span>, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample.&nbsp;</span><em>Indexcov</em><span>&nbsp;is available at&nbsp;</span><a href="https://github.com/brentp/goleft" target="_blank">https://github.com/brentp/goleft</a><span>&nbsp;under the MIT license.</span></p><p>Address of the bookmark: <a href="https://github.com/brentp/goleft" rel="nofollow">https://github.com/brentp/goleft</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39640/flas-fast-and-high-throughput-algorithm-for-pacbio-long-read-self-correction</guid>
	<pubDate>Sat, 22 Jun 2019 12:16:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39640/flas-fast-and-high-throughput-algorithm-for-pacbio-long-read-self-correction</link>
	<title><![CDATA[FLAS: fast and high throughput algorithm for PacBio long read self-correction.]]></title>
	<description><![CDATA[<p><span>FLAS, a wrapper algorithm of MECAT, to achieve high throughput long read self-correction while keeping MECAT's fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy.</span></p><p>Address of the bookmark: <a href="https://github.com/baoe/flas" rel="nofollow">https://github.com/baoe/flas</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations</guid>
	<pubDate>Sun, 15 Dec 2019 10:19:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations</link>
	<title><![CDATA[SeQuiLa-cov: A fast and scalable library for depth of coverage calculations]]></title>
	<description><![CDATA[<p><span>The Docker image is available at&nbsp;</span><a href="https://hub.docker.com/r/biodatageeks/" target="">https://hub.docker.com/r/biodatageeks/</a><span>. Supplementary information on benchmarking procedure as well as test data are publicly accessible at the project documentation site&nbsp;</span><a href="http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage" target="">http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage</a><span>. An archival copy of the code and supporting data is also available via the GigaScience database GigaDB</span></p>
<p>&bull; Project name: SeQuiLa-cov</p>
<p>&bull; Project home page:&nbsp;<a href="http://biodatageeks.org/sequila/" target="">http://biodatageeks.org/sequila/</a></p>
<p>&bull; Source code repository:&nbsp;<a href="https://github.com/ZSI-Bio/bdg-sequila" target="">https://github.com/ZSI-Bio/bdg-sequila</a></p>
<p>&bull; Operating system: Platform independent</p>
<p>&bull; Programming language: Scala</p>
<p>&bull; Other requirements: Docker</p>
<p>&bull; License: Apache License 2.0</p><p>Address of the bookmark: <a href="https://academic.oup.com/gigascience/article/8/8/giz094/5543653" rel="nofollow">https://academic.oup.com/gigascience/article/8/8/giz094/5543653</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</guid>
	<pubDate>Sun, 28 Dec 2014 12:51:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19980/seqloc-06</link>
	<title><![CDATA[seqloc 0.6]]></title>
	<description><![CDATA[<p>The <code>Bio.SeqLoc</code> modules in <code>seqloc</code> are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.</p>
<p>Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html</p><p>Address of the bookmark: <a href="http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6" rel="nofollow">http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6</a></p>]]></description>
	<dc:creator>Gudiya Pal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27331/andi</guid>
	<pubDate>Fri, 13 May 2016 05:16:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27331/andi</link>
	<title><![CDATA[Andi]]></title>
	<description><![CDATA[<p>This is the <code>andi</code> program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because <code>andi</code> does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.</p>
<p>This readme covers all necessary instructions for the impatient to get <code>andi</code> up and running. For extensive instructions please consult the <a href="https://github.com/EvolBioInf/andi/blob/master/andi-manual.pdf">manual</a>.</p>
<p>More at https://github.com/evolbioinf/andi/</p><p>Address of the bookmark: <a href="http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full" rel="nofollow">http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</guid>
	<pubDate>Thu, 23 Jun 2016 07:18:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</link>
	<title><![CDATA[Samtools Primer !!]]></title>
	<description><![CDATA[<p>SAMtools: Primer / Tutorial by Ethan Cerami, Ph.D.<br><br>keywords: samtools, next-gen, next-generation, sequencing, bowtie, sam, bam, primer, tutorial, how-to, introduction<br>Revisions<br><br>&nbsp;&nbsp;&nbsp; 1.0: May 30, 2013: First public release on biobits.org.<br>&nbsp;&nbsp;&nbsp; 1.1: July 24, 2013: Updated with Disqus Comments / Feedback section.<br>&nbsp;&nbsp;&nbsp; 1.2: December 19, 2014: Multiple updates, including:<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated to use samtools 1.1 and bcftools 1.2.<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated usage for bcftools.<br><br>About<br><br>SAMtools is a popular open-source tool used in next-generation sequence analysis. This primer provides an introduction to SAMtools, and is geared towards those new to next-generation sequence analysis. The primer is also designed to be self-contained and hands-on, meaning that you only need to install SAMtools, and no other tools, and sample data sets are provided. Terms in bold are also explained in the glossary at the end of the document.</p><p>Address of the bookmark: <a href="http://biobits.org/samtools_primer.html" rel="nofollow">http://biobits.org/samtools_primer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33479/novelseq-novel-sequence-insertion-detection</guid>
	<pubDate>Fri, 09 Jun 2017 04:31:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33479/novelseq-novel-sequence-insertion-detection</link>
	<title><![CDATA[NovelSeq: Novel Sequence Insertion Detection]]></title>
	<description><![CDATA[<p><span>The NovelSeq framework is designed to detect novel sequence insertions using high throughput paired-end whole genome sequencing data.</span></p>
<p>http://novelseq.sourceforge.net/Home</p>
<p>Paper at&nbsp;https://www.ncbi.nlm.nih.gov/pubmed/20385726</p><p>Address of the bookmark: <a href="http://novelseq.sourceforge.net/Home" rel="nofollow">http://novelseq.sourceforge.net/Home</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<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>

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