<?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/30102?offset=1130</link>
	<atom:link href="https://bioinformaticsonline.com/related/30102?offset=1130" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42917/fings-filters-for-next-generation-sequencing</guid>
	<pubDate>Sat, 27 Feb 2021 01:18:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42917/fings-filters-for-next-generation-sequencing</link>
	<title><![CDATA[FiNGS: Filters for Next Generation Sequencing]]></title>
	<description><![CDATA[<h2>Key features</h2>
<ul>
<li><strong>Filters SNVs from any variant caller to remove false positives</strong></li>
<li><strong>Calculates metrics based on BAM files and provides filtering not possible with other tools</strong></li>
<li><strong>Fully user-configurable filtering (including which filters to use and their thresholds)</strong></li>
<li><strong>Option to use filters identical to ICGC recommendations</strong></li>
</ul>
<p>FiNGS provides researchers with a tool to reproducibly filter somatic variants that is simple to both deploy and use, with filters and thresholds that are fully configurable by the user. It ingests and emits standard variant call format (VCF) files and will slot into existing sequencing pipelines. It allows users to develop and implement their own filtering strategies and simple sharing of these with others.</p>
<p>FiNGS reliably improves upon the precision of default variant caller outputs and performs better than other tools designed for the same task.</p><p>Address of the bookmark: <a href="https://github.com/cpwardell/FiNGS" rel="nofollow">https://github.com/cpwardell/FiNGS</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</guid>
	<pubDate>Sat, 27 Dec 2014 06:50:58 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/19820/rstudio</link>
	<title><![CDATA[RStudio]]></title>
	<description><![CDATA[<p>RStudio IDE is a powerful and productive user interface for R. It&rsquo;s free and open source, and works great on Windows, Mac, and Linux.</p>
<p>The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.</p>
<p>More at http://www.rstudio.com/</p>
<p>http://www.rstudio.com/products/RStudio/</p><p>Address of the bookmark: <a href="http://www.rstudio.com/" rel="nofollow">http://www.rstudio.com/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/45253/brava-browser</guid>
	<pubDate>Sun, 23 Aug 2026 10:32:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/45253/brava-browser</link>
	<title><![CDATA[BRaVa Browser]]></title>
	<description><![CDATA[<p>BRaVa Browser is an interactive web tool for exploring rare genetic variant associations. It allows users to search and visualize rare variant association results across genes and traits, making it easier to investigate potential relationships between genetic variation and disease or other phenotypes.</p>
<p>More at&nbsp;https://nikbaya.github.io/brava_browser/#/</p><p>Address of the bookmark: <a href="https://nikbaya.github.io/brava_browser/#/" rel="nofollow">https://nikbaya.github.io/brava_browser/#/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</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/37409/nanopolis-polish-a-genome-assembly</guid>
	<pubDate>Thu, 26 Jul 2018 04:51:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37409/nanopolis-polish-a-genome-assembly</link>
	<title><![CDATA[Nanopolis: polish a genome assembly]]></title>
	<description><![CDATA[<p><span>Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more (see Nanopolish modules, below).</span></p>
<p>Quickstart</p>
<p>http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html</p>
<p>Algorithms</p>
<p>http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/</p><p>Address of the bookmark: <a href="https://github.com/jts/nanopolish" rel="nofollow">https://github.com/jts/nanopolish</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20271/research-associate-tata-memorial-centre-advanced-centre-for-treatment-research-and-education-in-cancer-kharghar-navi-mumbai</guid>
  <pubDate>Thu, 08 Jan 2015 20:53:57 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate	@ TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI]]></title>
  <description><![CDATA[
<p>TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI – 410210</p>

<p>Website: www.actrec.gov.in; Ph: 27405000</p>

<p>No. ACTREC/Advt./ 66 /2014 23rd December, 2014<br />Research Associate	</p>

<p>International Cancer Genome Consortium (ICGC) - India Project (IRB Project No. 3 A/c. No. 2408)</p>

<p>Dr. Rajiv Sarin</p>

<p>Duration of the Project: One year Extendable up to Three years.</p>

<p>Consolidated Salary: Rs. 42,000/- p.m.</p>

<p>Application last date: 8th January, 2015.</p>

<p>Interview Date &amp; Time: 21st January, 2015, at 11.00 a.m.</p>

<p>Venue: Conference Room, 3rd floor, Khanolkar Shodhika, ACTREC.</p>

<p>Essential Qualifications and Experience:</p>

<p>Ph.D (any branch of Life Sciences)</p>

<p>The candidate must have at least one year experience after Ph.D., preferably in Genomics and Molecular Biology.</p>

<p>Candidates fulfilling these requirements should pre register themselves by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to icgc@actrec.gov.in latest 8th January, 2015 by 10.00 a.m.</p>

<p>Candidates shortlisted for the interview will be intimated by email on or before 9th January, 2015.</p>

<p>The interviews would be held on 21st January 2015 and will be only for the pre registered candidates who have been shortlisted.<br />No T.A./D.A. will be admissible for attending the interview.</p>

<p>At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.</p>

<p>Advertisement: www.actrec.gov.in/data%20files/2014/Walk-in-Research-Fellow-26-12-14.doc</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</guid>
	<pubDate>Thu, 04 Oct 2018 17:23:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop</link>
	<title><![CDATA[Long read assembly workshop !]]></title>
	<description><![CDATA[<p>This is a tutorial for a workshop on long-read (PacBio) genome assembly.</p>
<p>It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.</p>
<p>&nbsp;Please comment if you know any other long read addembly tutorial.</p><p>Address of the bookmark: <a href="http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/" rel="nofollow">http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/</a></p>]]></description>
	<dc:creator>Rahul Nayak</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/20471/bioinformatics-scripts</guid>
	<pubDate>Thu, 22 Jan 2015 22:29:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/20471/bioinformatics-scripts</link>
	<title><![CDATA[Bioinformatics Scripts]]></title>
	<description><![CDATA[<p>Some of the useful bioinformatics scripts.</p>
<p>For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.</p>
<p>http://milkweedgenome.org/?q=scripts</p><p>Address of the bookmark: <a href="http://milkweedgenome.org/?q=scripts" rel="nofollow">http://milkweedgenome.org/?q=scripts</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</guid>
	<pubDate>Fri, 24 Jan 2020 04:09:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization</link>
	<title><![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]></title>
	<description><![CDATA[<p><span>MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from&nbsp;</span><code>https://github.com/linzhi2013/MitoZ</code><span>.</span></p>
<p><span><a href="https://academic.oup.com/nar/article/47/11/e63/5377471">https://academic.oup.com/nar/article/47/11/e63/5377471</a></span></p><p>Address of the bookmark: <a href="https://github.com/linzhi2013/MitoZ" rel="nofollow">https://github.com/linzhi2013/MitoZ</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>