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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26303?offset=1510</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21538/senior-research-fellow-at-all-india-institute-of-medical-sciences-aiims-delhi-delhi-delhi</guid>
  <pubDate>Wed, 11 Mar 2015 03:06:10 -0500</pubDate>
  <link></link>
  <title><![CDATA[SENIOR RESEARCH FELLOW at All India Institute of Medical Sciences (AIIMS Delhi) - Delhi, Delhi]]></title>
  <description><![CDATA[
<p>Applications are invited from eligible candidates for the following temporary post in an ICMR funded Research Project entitle “An Investigation to find out reasons for Phenotypic Heterogeneity/Variability in 22q11.2 Microdeletion Syndrome” in Department of Reproductive Biology, AIIMS, New Delhi PI: Dr. Ashutosh Halder, Professor, Department of Reproductive Biology </p>

<p>Name of the post: Senior Research Fellow (SRF) <br />Duration: 2 year <br />Salary: Rs. 28000/- per month + 30% HRA <br />Eligibility: MSc (life sciences) with 2 years research experience, NET/GATE qualified <br />Desirable: Experience in the field of Genomics, Epigenomics &amp; Bioinformatics <br />SELECTION PROCEDURE FOR ALL INDIA INSTITUTE OF MEDICAL SCIENCES (AIIMS DELHI) – SENIOR RESEARCH FELLOW POST: </p>

<p>Candidates can apply on or before 15/03/2015 <br />No Detailed information about the selection process is mentioned in the recruitment notification <br />HOW TO APPLY FOR SENIOR RESEARCH FELLOW VACANCY IN ALL INDIA INSTITUTE OF MEDICAL SCIENCES (AIIMS DELHI): </p>

<p>Deadline: 15.03.15 Submit your C.V in Room No. 2099 (Molecular Cytogenetics Lab), 2nd floor, Reproductive Biology, All India Institute of Medical Sciences, New Delhi-110029 or Email CV to: ashutoshhalder@gmail.com Your CV should include the details of your work experience &amp; degrees along with two references with e-mail and contact number Only 10 shortlisted (on merit) candidates will be invited for interview. No TA/DA will be applicable for the same</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</guid>
	<pubDate>Wed, 29 Jan 2020 06:29:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping</link>
	<title><![CDATA[Understanding your reads and mapping !]]></title>
	<description><![CDATA[<p>One of the best tutorial for beginners ...</p>
<p>https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</p><p>Address of the bookmark: <a href="https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html" rel="nofollow">https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43550/basic-structure-of-snakemake-pipeline-run</guid>
	<pubDate>Thu, 14 Oct 2021 07:01:38 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43550/basic-structure-of-snakemake-pipeline-run</link>
	<title><![CDATA[Basic Structure of Snakemake Pipeline Run !]]></title>
	<description><![CDATA[<div>/user/snakemake-demo$ ls</div><div>config.json data envs scripts slurm-240702.out Snakefile</div><ul>
<li>data = mock data for the snakefile to use</li>
<li>Snakefile = name of the snakemake &ldquo;formula&rdquo; file
<ul>
<li>Note: The default file that snakemake looks for in the current working directory is the&nbsp;<code>Snakefile</code>. If you would like to override that you can specify it following the&nbsp;<code>-s</code>
<ul>
<li><code>snakemake -s snakefile.py</code></li>
</ul>
</li>
</ul>
</li>
<li>envs = directory for storing the conda environments that the workflow will use.</li>
<li>scripts = directory for storing python scripts called by the snakemake formula.</li>
<li>config.json = json format file with extra parameters for our snakemake file to use.</li>
<li>cluster.json = json format file with specification for running on the HPC</li>
<li>samples.txt = file we will use later relating to the config.json file.</li>
</ul><p><span>Run the snakemake file as a dry run (the example workflow shown above).</span></p><ul>
<li>This will build a DAG of the jobs to be run without actually executing them.</li>
<li><code>snakemake --dry-run</code></li>
</ul><p>User can e<span>xecute rules of interest.</span></p><ul>
<li><code>snakemake --dry-run all</code>&nbsp;VS.&nbsp;<code>snakemake --dry-run call</code>&nbsp;VS.&nbsp;<code>snakemake --dry-run bwa</code></li>
</ul><p><span>Run the snakemake file in order to produce an image of the DAG of jobs to be run.</span></p><ul>
<li><code>snakemake --dag | dot -Tsvg &gt; dag.svg</code>&nbsp;OR&nbsp;<code>snakemake --dag | dot -Tsvg &gt; dag.svg</code></li>
</ul><p>Run the snakemake (this time not as a dry run)</p><ol>
<li><code>snakemake --use-conda</code></li>
</ol>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44675/variant-calling-pipeline</guid>
	<pubDate>Sat, 19 Oct 2024 12:23:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44675/variant-calling-pipeline</link>
	<title><![CDATA[Variant Calling Pipeline]]></title>
	<description><![CDATA[<p dir="auto">The&nbsp;<a href="https://github.com/Tom-Jenkins/maerl-wgs-pipelines/blob/main/src/variantcalling.nf"><code>variantcalling.nf</code></a>&nbsp;nextflow script will take any number of samples with paired-end reads in FASTQ format, map reads using Bowtie2, process BAM files, and finally call variants using BCFtools v1.21 and/or Freebayes v1.3.6. If part of the pipeline is unsuccessful for a sample then these errors are ignored.</p>
<p dir="auto">Pipeline flowchart:</p>
<div dir="auto">
<div dir="auto">
<div>&nbsp;</div>
<div></div>
</div>
<div>&nbsp;</div>
<div dir="auto">
<h2 dir="auto">Dependencies (version tested)</h2>
<a href="https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md#dependencies-version-tested"></a></div>
<ul dir="auto">
<li>Nextflow (24.04.4)</li>
<li>Java (18.0.2.1)</li>
<li>Python (3.10)</li>
<li>Perl (5.32.1)</li>
<li>Bowtie2 (2.5.3)</li>
<li>SAMtools (1.19.2)</li>
<li>GATK4 (4.5)</li>
<li>BCFtools (1.21)</li>
<li>Freebayes (1.3.6)</li>
</ul>
</div><p>Address of the bookmark: <a href="https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md" rel="nofollow">https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</guid>
	<pubDate>Wed, 06 Dec 2017 01:05:21 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing</link>
	<title><![CDATA[HiC-Pro: an optimized and flexible pipeline for Hi-C data processing]]></title>
	<description><![CDATA[<p><span>HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.</span></p>
<p>&nbsp;</p>
<p>http://nservant.github.io/HiC-Pro/</p><p>Address of the bookmark: <a href="http://nservant.github.io/HiC-Pro/" rel="nofollow">http://nservant.github.io/HiC-Pro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</guid>
	<pubDate>Sun, 13 Jan 2019 06:27:28 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38666/mcat-motif-combining-and-association-tool</link>
	<title><![CDATA[MCAT: Motif Combining and Association Tool]]></title>
	<description><![CDATA[<p>This is a pipeline for finding motifs in fasta files.<br>It can be run from the command line as follows:</p>
<p>usage: orange_pipeline_refine.py [-h] [-w W] [--nmotifs NMOTIFS] [--iter ITER] [-c C]<br>[-s S] [-d] [-ff] [-v V]<br>positive_seq negative_seq</p>
<p>positional arguments:<br>positive_seq the fasta file for the positive sequences<br>negative_seq the fasta file for the negative sequences</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yanshen43/MCAT" rel="nofollow">https://github.com/yanshen43/MCAT</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21472/asst-professor-at-central-university-of-jharkhand-cuj</guid>
  <pubDate>Sun, 01 Mar 2015 01:17:52 -0600</pubDate>
  <link></link>
  <title><![CDATA[Asst. Professor at Central University of Jharkhand (CUJ)]]></title>
  <description><![CDATA[
<p>Central University of Jharkhand (CUJ) has issued a recruitment notification for the recruitment of Assistant Professor through recruitment notification – Central University of Jharkhand (CUJ) Recruitment 2015 –  Advt. No.: CUJ/Advt./14-15/15 Date: 26th Feb. 2015. Candidates who have completed M.Sc, Ph.D can apply for the new recruitment notification from Central University of Jharkhand (CUJ)</p>

<p>Central University of Jharkhand has been granted funds by the Department of Biotechnology (DBT), Govt. of India to establish “DBT-Boost to CUJ Interdisciplinary Life Sciences Departments for Education and Research” Applications are invited for the Assistant Professor on purely temporary basis. The appointments shall be initially for a period of one year, renewable every year depending on the satisfactory performance, till the end of project.</p>

<p>Position: ASSISTANT PROFESSOR (Total 03)<br />Salary: 45,000/- (fixed) per month<br />Essential Qualifications: i. Good academic record with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the master’s degree level with specialization in Biodiversity and Systematic/ Systems Biology/ Biophysics/ Bioinformatics from an Indian  University, or an equivalent degree from an accredited foreign university. ii. Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET. iii. Notwithstanding anything contained in i. and ii. candidates, who are or have been awarded Ph.D Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulation, 2009, shall be exempted from therequirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor. iv. NET/SLET/SET shall also not be required for such disciplines for which NET/SLET/SET in not conducted.<br />Desirable: Preference will be given to candidates having Ph.D in any of the above mentioned areas with NET</p>

<p>IMPORTANT DATES TO REMEMBER  :</p>

<p>Last Date to Apply for this job 24/3/2015</p>

<p>REFERENCE:</p>

<p>Central University of Jharkhand (CUJ) Recruitment 2015 –  Advt. No.: CUJ/Advt./14-15/15 Date: 26th Feb. 2015.</p>

<p>More at http://cuj.ac.in/careers.php</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41998/wgddetector-a-pipeline-for-detecting-whole-genome-duplication-events-using-the-genome-or-transcriptome-annotations</guid>
	<pubDate>Thu, 23 Jul 2020 05:52:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41998/wgddetector-a-pipeline-for-detecting-whole-genome-duplication-events-using-the-genome-or-transcriptome-annotations</link>
	<title><![CDATA[WGDdetector: a pipeline for detecting whole genome duplication events using the genome or transcriptome annotations]]></title>
	<description><![CDATA[<p><span>WGDdetector pipeline that integrates all analyses including gene family constructing, dS estimating and phasing, and outputting the dS values of each paralogs pairs processed with only one command. We further chose four species (</span><em>Arabidopsis thaliana</em><span>,<span>&nbsp;</span></span><em>Juglans regia</em><span>,<span>&nbsp;</span></span><em>Populus trichocarpa</em><span><span>&nbsp;</span>and<span>&nbsp;</span></span><em>Xenopus laevis</em><span>) representing herb, wood and animal, to test its practicability. Our final results showed a high degree of accuracy with the previous studies using both genome and transcriptome data.</span></p>
<p><span>More at <a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3</a></span></p><p>Address of the bookmark: <a href="https://github.com/yongzhiyang2012/wgddetector" rel="nofollow">https://github.com/yongzhiyang2012/wgddetector</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21624/ra-bioinformatics-at-ch-charan-singh-university-meerut</guid>
  <pubDate>Wed, 11 Mar 2015 09:07:07 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Ch. Charan Singh University, Meerut]]></title>
  <description><![CDATA[
<p>Ch. Charan Singh University, Meerut</p>

<p>http://molbiolabccsumrt.webs.com/</p>

<p>Applications are invited for one post of RA in a DBT funded research project “Creation of Bioinformatics Infrastructure Facility (BIF) for the promotion of Biology Teaching through Bioinformatics (BTBI) Scheme of BTISet”.</p>

<p>Candidate should have a Ph.D. degree in Bioinformatics/Biotechnology/Genetics and Plant Breeding with adequate experience in the area of Bioinformatics. If a suitable candidate for the post of RA is not available, a JRF/SRF may be appointed.</p>

<p>Candidate for the post of JRF/SRF should have Master’s degree in relevant subject with adequate experience in the area of Bioinformatics and should be NET/DBT-BINC qualified</p>

<p>Interested candidates may send their bio-data to Prof. H. S. Balyan (hsbalyan@gmail.com) (in exceptional case, bio-data may also be submitted at the time of interview) and attend the interview on Monday, March 30, 2015 at 11:00 AM in the Department of Genetics &amp; Plant Breeding, Ch. Charan Singh University, Meerut. Candidates shall bring their original documents at the time of interview for verification. No interview letters will be issued and no TA/DA will be paid.</p>
]]></description>
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