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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28303?offset=220</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</guid>
	<pubDate>Fri, 10 Mar 2017 08:51:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</link>
	<title><![CDATA[sequenceserver]]></title>
	<description><![CDATA[<p><span>SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.</span></p>
<p><span><span>More at&nbsp;</span><a href="http://sequenceserver.com/">http://sequenceserver.com</a><span>.</span></span></p><p>Address of the bookmark: <a href="https://github.com/wurmlab/sequenceserver" rel="nofollow">https://github.com/wurmlab/sequenceserver</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32481/sspace</guid>
	<pubDate>Fri, 05 May 2017 05:42:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32481/sspace</link>
	<title><![CDATA[SSPACE]]></title>
	<description><![CDATA[<p>SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE" rel="nofollow">https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</guid>
	<pubDate>Tue, 03 Jul 2018 05:05:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37230/navigator-network-analysis-visualization-and-graphing-toronto</link>
	<title><![CDATA[NAViGaTOR: Network Analysis, Visualization and Graphing Toronto]]></title>
	<description><![CDATA[NAViGaTOR –  Network Analysis, Visualization, &amp; Graphing TORonto is a software system for scaleable visualizing and analyzing networks.

The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms.

http://142.150.188.236/navigatorwp/<p>Address of the bookmark: <a href="http://142.150.188.236/navigatorwp/" rel="nofollow">http://142.150.188.236/navigatorwp/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</guid>
	<pubDate>Fri, 30 Jun 2017 08:48:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33741/diya-a-bacterial-annotation-pipeline-for-any-genomics-lab</link>
	<title><![CDATA[DIYA: a bacterial annotation pipeline for any genomics lab]]></title>
	<description><![CDATA[<p><span>DIY Genomics is an open source bioinformatics consortium intended to bring a collection of tools and libraries into the hands of small scale genomics labs for the process of sequence assembly and annotation. Projects include DIYA, MGAP, CRISPR, and DIYGV</span></p>
<p><span>http://gmod.org/wiki/Diya</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/diyg/" rel="nofollow">https://sourceforge.net/projects/diyg/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37982/raven-a-software-suite-for-matlab-that-allows-for-semi-automated-reconstruction-of-genome-scale-models</guid>
	<pubDate>Wed, 24 Oct 2018 22:38:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37982/raven-a-software-suite-for-matlab-that-allows-for-semi-automated-reconstruction-of-genome-scale-models</link>
	<title><![CDATA[RAVEN: a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models]]></title>
	<description><![CDATA[<p><span>The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc databases, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology.</span></p><p>Address of the bookmark: <a href="https://github.com/SysBioChalmers/RAVEN" rel="nofollow">https://github.com/SysBioChalmers/RAVEN</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/34368/srbioinformatics-analyst-ngs-at-ocimum</guid>
  <pubDate>Fri, 17 Nov 2017 07:50:44 -0600</pubDate>
  <link></link>
  <title><![CDATA[Sr.Bioinformatics Analyst (NGS) at Ocimum]]></title>
  <description><![CDATA[
<p>JOB FUNCTIONBio Tech/R&amp;D/Scientist<br />INDUSTRYBiotechnology/Pharmaceutical/Medicine<br />SPECIALIZATIONBasic Research,Bio-Statistician,Clinical Research<br />QUALIFICATION<br />Any Post Graduate<br />BA (Arts), B.Com. (Commerce), BE/ B.Tech (Engineering), B.Pharm. (Pharmacy), B.Sc. (Science), BL/LLB, BDS (Dental Surgery), B.Ed. (Education), BHM (Hotel Management), BBA/ BBM/ BBS, B.Arch. (Architecture), BCA (Computer Application), Diploma-Other Diploma, B.Plan. (Planning), BGL, B.V.Sc. (Veterinary Science), Other School/ Graduation, BHMS (Homeopathy), BAMS (Ayurveda)<br />Job Description</p>

<p>1.  Must have basic understanding of molecular biology and Genomics.<br />2. Experience in application development or must have expertise in programming using either of Perl/Python.<br />3.  Experience in statistical programming using R/Bioconductor/Matlab.<br />4. Strong concept in statistical and mathematical modelling.<br />5.  Experience in designing and developing the bioinformatics pipeline.<br />6.  Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.<br />7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.<br />8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.<br />9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.<br />10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.<br />11. Ability to work as team as well as independently with minimal support.</p>

<p>More at http://www3.ocimumbio.com/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/36197/bioinformatics-oneliner</guid>
	<pubDate>Tue, 10 Apr 2018 04:13:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/36197/bioinformatics-oneliner</link>
	<title><![CDATA[Bioinformatics OneLiner]]></title>
	<description><![CDATA[<p>To remove all line ends (\n) from a Unix text file:</p><pre>sed ':a;N;$!ba;s/\n//g' filename.txt &gt; newfilename_oneline.txt</pre><p>To get average for a column of numbers (here the second column $2):</p><pre>awk '{ sum += $2; n++ } END { if (n &gt; 0) print sum / n; }'</pre><p>To get sequence length for all sequences in a fasta file:</p><pre>awk '/^&gt;/ {if (seqlen){print seqlen}; print ;seqlen=0;next; } { seqlen = seqlen +length($0)}END{print seqlen}' \<br />filename.fasta</pre><p>To copy (move, rename, etc) files based on their list in a text file:</p><pre>cat file_list.txt | while read line; do cp "$line" complete_dataset/"$line"; done</pre><p>To split bam files into sets with mapped and unmapped reads:</p><pre>samtools view -F4 sample.bam &gt; sample.mapped.sam<br />samtools view -f4 sample.bam &gt; sample.unmapped.sam</pre><p>To gzip all your fastq files using gnu parallel and gzip:</p><pre>parallel gzip ::: *.fastq</pre><p>To gzip all your fastq files using pigz:</p><pre>pigz *.fastq</pre><p>To count all sequences in a fasta file:</p><pre>grep "^&gt;" yourfile.fasta -c</pre><p>To count all sequences in all fasta files in your current directory:</p><pre>for a in *.fasta; do ls $a; grep "^&gt;" -c $a; done</pre><p>To keep only one copy of duplicated lines:</p><pre>awk '!seen[$0]++'</pre><p>To sum assembly size from SPAdes contigs.fasta or scaffolds.fasta file:</p><pre>grep "^&gt;" scaffolds.fasta | cut -f 4 -d '_' | paste -sd+ | bc</pre><p>To remove everything after the first space at each line, e.g. to to simplify fasta headers:</p><pre>cut -d' ' -f1 &lt; your_file</pre><p>To count reads in a all .fastq.gz files in your current folder (fast, using gnu parallel):</p><pre>parallel "echo {} &amp;&amp; gunzip -c {} | wc -l | awk '{d=\$1; print d/4;}'" ::: *.gz</pre><p>To count reads in a all .fastq.gz files in your current folder:</p><pre>zcat *.gz | echo $((`wc -l`/4))</pre><p>To count reads in a all .fastq files in your current folder:</p><pre>cat *.fastq | echo $((`wc -l`/4))</pre><p>To count base pairs in a all .fastq.gz files in your current folder:</p><pre>zcat *.fastq.gz | paste - - - - | cut -f 2 | tr -d '\n' | wc -c </pre><p>To split multifasta file into many fasta files:</p><pre>awk '/^&gt;/ {OUT=substr($0,2) ".fa"}; {print &gt;&gt; OUT; close(OUT)}' Input_File</pre><p>To convert Illumina FASTQ 1.3 to 1.8:</p><pre>sed -e '4~4y/@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghi/!"#$%&amp;'\''()*+,-.\/0123456789:;&lt;=&gt;?@ABCDEFGHIJ/' f.fastq</pre><p>To convert FASTQ to FASTA:</p><pre>sed -n '1~4s/^@/&gt;/p;2~4p' </pre><p>To get fastq read length distribution:</p><pre>cat reads.fastq | awk '{if(NR%4==2) print length($1)}' | sort | uniq -c</pre><p>To deinterleave interleaved fastq file:</p><pre>cat myf.fq | paste - - - - - - - - | tee &gt;(cut -f 1-4 | tr "\t" "\n" &gt; myfile_1.fq) | cut -f 5-8 | \<br />tr "\t" "\n" &gt; myf2.fq </pre><p>To filter and sort contig identifiers from SPAdes assembly (e.g. here lenght &gt;= 4000 + coverage &gt;=100):</p><pre>grep "^&gt;" scaffolds.fasta | sed s"/_/ /"g | awk '{ if ($4 &gt;= 4000 &amp;&amp; $6 &gt;= 100) print $0 }' | sort -k 4 -n | \<br />sed s"/ /_/"g</pre><p>To append something to all headers of your fasta files:</p><pre>sed 's/&gt;.*/&amp;YOURSTRING/' filename.fasta &gt; new_filename.fasta</pre><p>To replace/squeeze multiple adjacent spaces by only one space:&nbsp;</p><pre>tr -s " " &lt; file</pre><p>To filter fastq based on length (here larger than or equal to 21, but smaller than or equal to 25.</p><pre>cat your.fastq | paste - - - - | awk 'length($2)&nbsp; &gt;= 21 &amp;&amp; length($2) &lt;= 25' | sed 's/\t/\n/g' &gt; filtered.fastq</pre><p>To print difference between the last and first row in 5th column:</p><pre>awk '{if (!first){first=$5;}; last=$5;} END {print last-first}' myfile.txt</pre><p>To sample only 200 first bases from all sequences in a multifasta file (e.g. from assembly scaffolds.fasta file here):</p><pre>awk '/^&gt;/{ seqlen=0; print; next; } seqlen &lt; 200 { if (seqlen + length($0) &gt; 200) $0 = substr($0, 1, 200-seqlen);\<br /> seqlen += length($0); print }' scaffolds.fasta &gt; 200bp_scaffolds.fasta</pre><p>&nbsp;To pipe a compressed fasta file directly into makeblastdb.</p><pre>gunzip -c fasta.gz | makeblastdb -in -</pre><p>To remove sequences with duplicate fasta headers from a fasta file.</p><pre>awk '/^&gt;/{f=!d[$1];d[$1]=1}f' in.fasta &gt; out.fasta</pre>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</guid>
	<pubDate>Wed, 20 Dec 2017 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</link>
	<title><![CDATA[Delta: a new Web-based 3D genome visualization and analysis platform]]></title>
	<description><![CDATA[<p><em>Delta</em><span>&nbsp;is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes.&nbsp;</span><em>Delta</em><span>&nbsp;takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome.&nbsp;</span><em>Delta</em><span>features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.</span></p>
<p>https://github.com/zhangzhwlab/delta</p><p>Address of the bookmark: <a href="https://github.com/zhangzhwlab/delta" rel="nofollow">https://github.com/zhangzhwlab/delta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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