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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/23167?offset=120</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</guid>
	<pubDate>Mon, 28 May 2018 09:41:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36806/manta-rapid-detection-of-structural-variants-and-indels-for-germline-and-cancer-sequencing-applications</link>
	<title><![CDATA[Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications.]]></title>
	<description><![CDATA[Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. Manta discovers, assembles and scores large-scale SVs, medium-sized indels and large insertions within a single efficient workflow.<p>Address of the bookmark: <a href="https://github.com/Illumina/manta" rel="nofollow">https://github.com/Illumina/manta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</guid>
	<pubDate>Mon, 06 Aug 2018 17:24:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37498/nextsv-a-meta-caller-for-structural-variants-from-low-coverage-long-read-sequencing-data</link>
	<title><![CDATA[NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data]]></title>
	<description><![CDATA[<p>NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purpose. The output of NextSV is in ANNOVAR-compatible bed format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer.</p>
<p>&nbsp;</p>
<h2>&nbsp;</h2><p>Address of the bookmark: <a href="https://github.com/Nextomics/NextSV" rel="nofollow">https://github.com/Nextomics/NextSV</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</guid>
	<pubDate>Thu, 06 Sep 2018 16:21:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37643/lorma-a-tool-for-correcting-sequencing-errors-in-long-reads</link>
	<title><![CDATA[LoRMA: A tool for correcting sequencing errors in long reads]]></title>
	<description><![CDATA[<p><span>An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of&nbsp;</span><em>k</em><span>-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75&times;, the throughput of the new method is at least 20% higher.</span></p>
<blockquote>
<p><span>conda install -c atgc-montpellier lorma</span></p>
</blockquote><p>Address of the bookmark: <a href="https://gite.lirmm.fr/lorma/lorma-releases/wikis/home" rel="nofollow">https://gite.lirmm.fr/lorma/lorma-releases/wikis/home</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</guid>
	<pubDate>Thu, 04 Oct 2018 05:23:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37830/nquire-a-statistical-framework-for-ploidy-estimation-using-next-generation-sequencing</link>
	<title><![CDATA[nQuire: a statistical framework for ploidy estimation using next generation sequencing]]></title>
	<description><![CDATA[<p>nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.</p><p>Address of the bookmark: <a href="https://github.com/clwgg/nQuireunder" rel="nofollow">https://github.com/clwgg/nQuireunder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</guid>
	<pubDate>Tue, 27 Nov 2018 04:43:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data</link>
	<title><![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]></title>
	<description><![CDATA[<p><span>lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.</span></p>
<p>lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/lordfast" rel="nofollow">https://github.com/vpc-ccg/lordfast</a></p>]]></description>
	<dc:creator>BioJoker</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/40251/mosdepth-fast-bamcram-depth-calculation-for-wgs-exome-or-targeted-sequencing</guid>
	<pubDate>Wed, 13 Nov 2019 22:20:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40251/mosdepth-fast-bamcram-depth-calculation-for-wgs-exome-or-targeted-sequencing</link>
	<title><![CDATA[mosdepth: fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing]]></title>
	<description><![CDATA[<p>mosdepth can output:</p>
<p>per-base depth about 2x as fast samtools depth--about 25 minutes of CPU time for a 30X genome.<br>mean per-window depth given a window size--as would be used for CNV calling.<br>the mean per-region given a BED file of regions.<br>a distribution of proportion of bases covered at or above a given threshold for each chromosome and genome-wide.<br>quantized output that merges adjacent bases as long as they fall in the same coverage bins e.g. (10-20)<br>threshold output to indicate how many bases in each region are covered at the given thresholds.<br>A summary of mean depths per chromosome and within specified regions per chromosome.</p><p>Address of the bookmark: <a href="https://github.com/brentp/mosdepth" rel="nofollow">https://github.com/brentp/mosdepth</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</guid>
	<pubDate>Tue, 28 Jan 2020 03:27:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40701/fastgt-an-alignment-free-method-for-calling-common-snvs-directly-from-raw-sequencing-reads</link>
	<title><![CDATA[FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads]]></title>
	<description><![CDATA[<p>FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.</p>
<p><a href="http://bioinfo.ut.ee/FastGT/">http://bioinfo.ut.ee/FastGT/</a></p>
<p><strong><a href="https://github.com/bioinfo-ut/GenomeTester4/">https://github.com/bioinfo-ut/GenomeTester4/</a></strong></p><p>Address of the bookmark: <a href="http://bioinfo.ut.ee/FastGT/" rel="nofollow">http://bioinfo.ut.ee/FastGT/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</guid>
	<pubDate>Mon, 04 May 2020 02:04:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads</link>
	<title><![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]></title>
	<description><![CDATA[<p><span>HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.</span></p><p>Address of the bookmark: <a href="https://github.com/vpc-ccg/haslr" rel="nofollow">https://github.com/vpc-ccg/haslr</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</guid>
	<pubDate>Thu, 11 Feb 2021 21:39:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</link>
	<title><![CDATA[Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data]]></title>
	<description><![CDATA[<p>Ktrim&nbsp;is written in&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">C++</code>&nbsp;for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">ktrim</code>&nbsp;under&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">bin/</code>&nbsp;directory compiled using&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">g++ v4.8.5</code>&nbsp;and linked with&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz v1.2.7</code>&nbsp;for Linux x86_64 system. If you could not run it (which is usually caused by low version of&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libc++</code>&nbsp;or&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz</code>&nbsp;library) or you want to build a version optimized for your system, you can re-compile the programs:</p>
<p>user@linux$ make clean &amp;&amp; make</p><p>Address of the bookmark: <a href="https://github.com/hellosunking/Ktrim" rel="nofollow">https://github.com/hellosunking/Ktrim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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