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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44481?offset=80</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</guid>
	<pubDate>Sat, 22 Aug 2020 05:58:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42150/parallellastz-lastz-with-multi-threads-support</link>
	<title><![CDATA[parallelLastz: Lastz with multi-threads support.]]></title>
	<description><![CDATA[<p>Running Lastz (<a href="https://github.com/lastz/lastz">https://github.com/lastz/lastz</a>) in parallel mode. This program is for single computer with multiple core processors.</p>
<p>When the query file format is fasta, you can specify many threads to process it. It can reduce run time linearly, and use almost equal memory as the original lastz program. This is useful when you lastz a big query file to a huge reference like human whole genome sequence.</p>
<p>The program is an extension on the original lastz program which was written by Bob Harris (the LASTZ guy).</p><p>Address of the bookmark: <a href="https://github.com/jnarayan81/parallelLastz" rel="nofollow">https://github.com/jnarayan81/parallelLastz</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Tue, 02 Apr 2019 21:54:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39213/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</guid>
	<pubDate>Tue, 12 Dec 2017 17:23:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34618/mashmap-a-fast-and-approximate-software-for-mapping-long-reads-pacbioont-or-assembly-to-reference-genomes</link>
	<title><![CDATA[MashMap: a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s)]]></title>
	<description><![CDATA[<p><span>MashMap is a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s). It maps a query sequence against a reference region if and only if its estimated alignment identity is above a specified threshold. It does not compute the alignments explicitly, but rather estimates a&nbsp;</span><em>k</em><span>-mer based&nbsp;</span><a href="https://en.wikipedia.org/wiki/Jaccard_index">Jaccard similarity</a><span>&nbsp;using a combination of&nbsp;</span><a href="http://www.cs.princeton.edu/courses/archive/spr05/cos598E/bib/p76-schleimer.pdf">Winnowing</a><span>&nbsp;and&nbsp;</span><a href="https://en.wikipedia.org/wiki/MinHash">MinHash</a><span>. This is then converted to an estimate of sequence identity using the&nbsp;</span><a href="http://mash.readthedocs.org/">Mash</a><span>&nbsp;distance. An appropriate&nbsp;</span><em>k</em><span>-mer sampling rate is automatically determined given minimum local alignment length and identity thresholds. The efficiency of the algorithm improves as both of these thresholds are increased.</span></p><p>Address of the bookmark: <a href="https://github.com/marbl/MashMap" rel="nofollow">https://github.com/marbl/MashMap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37302/fastani-fast-alignment-free-computation-of-whole-genome-average-nucleotide-identity-ani</guid>
	<pubDate>Fri, 13 Jul 2018 17:27:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37302/fastani-fast-alignment-free-computation-of-whole-genome-average-nucleotide-identity-ani</link>
	<title><![CDATA[FastANI:  fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI)]]></title>
	<description><![CDATA[<p><span>FastANI is developed for fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI). ANI is defined as mean nucleotide identity of orthologous gene pairs shared between two microbial genomes. FastANI supports pairwise comparison of both complete and draft genome assemblies. Its underlying procedure follows a similar workflow as described by&nbsp;</span><a href="http://www.ncbi.nlm.nih.gov/pubmed/17220447">Goris et al. 2007</a><span>. However, it avoids expensive sequence alignments and uses&nbsp;</span><a href="https://github.com/marbl/MashMap">Mashmap</a><span>&nbsp;as its MinHash based sequence mapping engine to compute the orthologous mappings and alignment identity estimates. Based on our experiments with complete and draft genomes, its accuracy is on par with&nbsp;</span><a href="http://enve-omics.ce.gatech.edu/ani/">BLAST-based ANI solver</a><span>&nbsp;and it achieves two to three orders of magnitude speedup. Therefore, it is useful for pairwise ANI computation of large number of genome pairs. More details about its speed, accuracy and potential applications are described here: "</span><a href="https://doi.org/10.1101/225342">High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries</a><span>".</span></p><p>Address of the bookmark: <a href="https://github.com/ParBLiSS/FastANI" rel="nofollow">https://github.com/ParBLiSS/FastANI</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37606/stellar-fast-and-exact-local-alignments</guid>
	<pubDate>Wed, 29 Aug 2018 16:00:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37606/stellar-fast-and-exact-local-alignments</link>
	<title><![CDATA[STELLAR: fast and exact local alignments]]></title>
	<description><![CDATA[<p><span>STELLAR is very practical and fast on very long sequences which makes it a suitable new tool for finding local alignments between genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows, and Mac OS X at&nbsp;</span><span><a href="http://www.seqan.de/projects/stellar"><span>http://www.seqan.de/projects/stellar</span></a></span><span>.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.seqan.de/apps/stellar/" rel="nofollow">http://www.seqan.de/apps/stellar/</a></p>]]></description>
	<dc:creator>Neel</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/43639/fastv-detect-virus</guid>
	<pubDate>Sat, 11 Dec 2021 08:04:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43639/fastv-detect-virus</link>
	<title><![CDATA[fastv - detect virus]]></title>
	<description><![CDATA[<p><span>fastv is an ultra-fast tool for identification of SARS-CoV-2 and other microbes from sequencing data. It detects microbial sequences from FASTQ data, generates JSON reports and visualizes the result in HTML reports. This tool can be used to detect viral infectious diseases, like COVID-19. This tool supports both short reads (Illumina, BGI, etc.) and long reads (ONT, PacBio, etc.)</span></p><p>Address of the bookmark: <a href="https://github.com/OpenGene/fastv" rel="nofollow">https://github.com/OpenGene/fastv</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</guid>
	<pubDate>Sun, 31 Aug 2025 06:30:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44896/jaeger-an-accurate-and-fast-deep-learning-tool-to-detect-bacteriophage-sequences</link>
	<title><![CDATA[Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences]]></title>
	<description><![CDATA[<p><span>Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.</span></p><p>Address of the bookmark: <a href="https://github.com/MGXlab/Jaeger" rel="nofollow">https://github.com/MGXlab/Jaeger</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36616/srbreak-a-read-depth-and-split-read-framework-to-identify-breakpoints-of-different-events-inside-simple-copy-number-variable-regions</guid>
	<pubDate>Tue, 15 May 2018 04:42:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36616/srbreak-a-read-depth-and-split-read-framework-to-identify-breakpoints-of-different-events-inside-simple-copy-number-variable-regions</link>
	<title><![CDATA[SRBreak: A Read-Depth and Split-Read Framework to Identify Breakpoints of Different Events Inside Simple Copy-Number Variable Regions]]></title>
	<description><![CDATA[SRBreak is a read-depth and split-read package written in R for identifying copy-number variants in next-generation sequencing datasets.

Note: SBReak was designed to work for multiple samples. It can work for &gt;= 2 samples, but we suggest that users should use &gt;= 5 samples as in the work tested in our paper.<p>Address of the bookmark: <a href="https://github.com/hoangtn/SRBreak" rel="nofollow">https://github.com/hoangtn/SRBreak</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36015/repeat-aware-repeat-aware-scaffolding-evaluation-framework-by-igor-mandric</guid>
	<pubDate>Wed, 21 Mar 2018 18:10:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36015/repeat-aware-repeat-aware-scaffolding-evaluation-framework-by-igor-mandric</link>
	<title><![CDATA[repeat-aware: Repeat aware scaffolding evaluation framework by Igor Mandric]]></title>
	<description><![CDATA[<p>Genome scaffolding is a classical challenging problem in bioinformatics. It refers to joining assembly contigs into chains (called scaffolds). The join between two contigs A and B is considered correct if:</p>
<ul>
<li>Their relative orientation is correct</li>
<li>Their relative order is correct</li>
<li>The gap estimate is similar to the true distance on the reference</li>
</ul>
<p>The problem of scaffolding validation is also a challenging one. One of the main issues which hinders from an adequate scaffolding evaluation are genome repeats. The previous standard for evaluation&nbsp;<a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2014-15-3-r42">(Hunt et al.,&nbsp;<em>Genome Biology</em>, 2014)</a>&nbsp;did not take into account repeats. In this evaluation framework, repeats are taken into account.</p>
<p style="text-align: center;"><a href="https://camo.githubusercontent.com/9675b90205e5bc0dc0b6b84b321b00bc87d8d88e/687474703a2f2f616c616e2e63732e6773752e6564752f7265706561742d61776172652f6669677572652e706e67" target="_blank"><img src="https://camo.githubusercontent.com/9675b90205e5bc0dc0b6b84b321b00bc87d8d88e/687474703a2f2f616c616e2e63732e6773752e6564752f7265706561742d61776172652f6669677572652e706e67" width="75%" alt="image" style="border: 0px;"></a></p>
<p>The new evaluation framework considers the optimal assignment of contigs in the output scaffolding to contigs in the reference scaffolding in the sense of the number of correct links.</p>
<p>&nbsp;</p>
<p>https://github.com/mandricigor/repeat-aware</p><p>Address of the bookmark: <a href="https://github.com/mandricigor/repeat-aware" rel="nofollow">https://github.com/mandricigor/repeat-aware</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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