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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29280?offset=1240</link>
	<atom:link href="https://bioinformaticsonline.com/related/29280?offset=1240" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</guid>
	<pubDate>Thu, 30 May 2019 04:06:13 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39441/snakepipes-a-toolkit-based-on-snakemake-and-python-for-analysis-of-ngs-data</link>
	<title><![CDATA[snakepipes: A toolkit based on snakemake and python for analysis of NGS data]]></title>
	<description><![CDATA[<p><span><span>snakePipes are flexible and powerful workflows built using&nbsp;</span><a href="https://github.com/maxplanck-ie/snakepipes/blob/master/snakemake.readthedocs.io">snakemake</a><span>&nbsp;that simplify the analysis of NGS data.</span></span></p>
<ul>
<li>DNA-mapping*</li>
<li>ChIP-seq*</li>
<li>RNA-seq*</li>
<li>ATAC-seq*</li>
<li>scRNA-seq</li>
<li>Hi-C</li>
<li>Whole Genome Bisulfite Seq/WGBS</li>
</ul>
<p><span>(*Also available in "allele-specific" mode)</span></p>
<p><span>snakePipes can be installed via conda : </span></p>
<p><span>'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'. </span></p>
<p><span>Source code (</span><a href="https://github.com/maxplanck-ie/snakepipes" target="">https://github.com/maxplanck-ie/snakepipes</a><span>) and documentation (</span><a href="https://snakepipes.readthedocs.io/en/latest/" target="">https://snakepipes.readthedocs.io/en/latest/</a><span>) are available online.</span></p><p>Address of the bookmark: <a href="https://github.com/maxplanck-ie/snakepipes" rel="nofollow">https://github.com/maxplanck-ie/snakepipes</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22965/ra-bioinformatics-at-bharathidasan-university</guid>
  <pubDate>Sun, 28 Jun 2015 12:21:48 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at Bharathidasan University]]></title>
  <description><![CDATA[
<p>National Facility for Marine Cyanobacteria <br />Department of Marine Biotechnology <br />Bharathidasan University <br />Tiruchirappalli -620024, Tamil Nadu </p>

<p>Applications are invited from individuals who have high motivation to do research for the below mentioned position, </p>

<p>1. Research Associate - 1 No. <br />in the DBT sponsored project under the supervision of Dr. D. Prabaharan, Principal Investigator, National Facility for Marine Cyanobacteria, Dept. of Marine Biotechnology, Bharathidasan University, Tiruchirappalli-24. </p>

<p>Title of the Project: “Establishment of National Repository for Micro algae &amp; Cyanobacteria” funded by Department of Biotechnology, Govt. of India </p>

<p>Qualification </p>

<p>1. Research Associate – 1 No. Rs. 36,000/38,000/40,000 per month for I, II and III year + 20% HRA </p>

<p>Essential : Doctoral degree in relevant subject from recognized University/ Institutes <br />Desirable: Research experience in molecular biology and bioinformatics </p>

<p>Interested candidates can send their complete CV in plain paper with a passport size photograph, with details of Marks secured in all subjects from plus two stage (with proof, full postal address, sex, date of birth, community etc., along with additional qualification or experiences and two address of references whom could be contacted (One of whom should be PG teacher/guide). Application should reach the Principal Investigator on or before 30.06.2015 by Email (nfmcbic@yahoo.com)/Registered post/ Speed post, with subject subscribed as “Application for Research Associate /Technical Assistant /Lab attendant”. Qualifying candidates will be short listed and communicated with date of interview. No TA and DA will be given for attending the interview. Addressfor Communication Dr. D. Prabaharan Principal Investigator National Facility for Marine Cyanobacteria Bharathidasan University Tiruchirappalli-620024, Tamil Nadu.</p>

<p>Advertisement: http://www.bdu.ac.in/adv/NFMC_Project_Positions.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</guid>
	<pubDate>Fri, 24 Jan 2020 06:04:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output</link>
	<title><![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]></title>
	<description><![CDATA[<p><span>gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser. </span></p>
<p><span>gapFinisher can fill gaps in draft genomes quickly and reliably.</span></p><p>Address of the bookmark: <a href="https://github.com/kammoji/gapFinisher" rel="nofollow">https://github.com/kammoji/gapFinisher</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</guid>
	<pubDate>Thu, 28 May 2020 21:57:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data</link>
	<title><![CDATA[Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data]]></title>
	<description><![CDATA[<p>Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.</p>
<p>Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.</p><p>Address of the bookmark: <a href="https://github.com/dnanexus/parliament2" rel="nofollow">https://github.com/dnanexus/parliament2</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23627/ra-bioinformatics-at-nipgr</guid>
  <pubDate>Tue, 04 Aug 2015 18:53:29 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at NIPGR]]></title>
  <description><![CDATA[
<p>Applications are invited from suitable candidates for filling up one position of Research Associate (RA) in the Institute with Dr. Senthil-Kumar Muthappa, Scientist, NIPGR, in the scheme of "Short-Term Research Fellowship" programme. The position is completely on temporary basis with maximum duration of three years. The initial appointment will be for a period of one year, which can be curtailed or extended based on the performance of the candidate and discretion of the Competent Authority.</p>

<p>The candidate is expected to have experience in handling functional genomics tools to dissect defense responses against bacterial pathogens and drought stress tolerance. This project may involve use of bioinformatics tools, database development, large scale transcriptome profiling, virus-induced gene silencing and any other research work as assigned by the PI.</p>

<p>Qualification: Candidates having a Ph. D. degree in Bioinformatics/Plant Molecular Biology/Plant Physiology/Plant Pathology/Plant Breeding &amp; Genetics and strong publication record can apply. Candidates having prior work experience in using advanced molecular biology tools in laboratory with strong bioinformatics knowledge are preferred.</p>

<p>The Fellowship amount for the position will be given at par with the similar fellowships by DBT/DST.</p>

<p>NIPGR reserves the right to select the candidate against the above post depending upon the qualifications and experience of the candidate. Reservation of post shall be as per Govt. of India norms.</p>

<p>Eligible candidates may apply by sending hard copy of complete application in the given format with a cover letter showing interest and specifying the position. The attested copies of the mark-sheets, certificates, proof of research experience/publications are to be attached. The application should reach at the address given below within 15 days from the date of advertisement. The envelope must be superscribed by "Application for the post of RA under NIPGR Short-term research fellowship programme". No TA/DA will be paid for attending the interview.</p>

<p>ONLY hard copy of the application in the given format will be accepted.<br />www.nipgr.res.in/files/careers/format_RA2.doc</p>

<p>Dr. Senthil-Kumar Muthappa<br />Staff Scientist - III,<br />National Institute of Plant Genome Research (NIPGR)<br />Aruna Asaf Ali Marg, P.O. Box NO. 10531,<br />New Delhi - 110067</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/43227/project-associate-i-project-associate-ii-senior-project-associate-igib</guid>
  <pubDate>Thu, 05 Aug 2021 16:11:32 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Associate-I | Project Associate-II | Senior Project Associate @ IGIB]]></title>
  <description><![CDATA[
<p>Experience in Next Generation Sequencing (NGS) application and interest in Genomics/ Clinical / Translational Applications. OR Good computational programming skills and deep interest in working on interface of Genomics and Clinical application. </p>

<p>Project Scientist-I <br />Experimental / Computation analysis experience in highthroughput genomics/ clinical application.</p>

<p>Project Manager <br />Experience in handling large biological projects involving high-throughput genomics/ clinical application.</p>

<p>Scientific Administrative Assistant <br />Lab Work. </p>

<p>More at https://vinodscaria.genomes.in/positionsopen</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming</guid>
	<pubDate>Thu, 02 Jan 2025 20:11:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming</link>
	<title><![CDATA[The &quot;Ifs&quot; and &quot;Buts&quot; of NGS Quality Control and Trimming]]></title>
	<description><![CDATA[<p>Next-Generation Sequencing (NGS) has revolutionized biological research, providing vast amounts of data for a wide range of applications. However, the reliability of NGS analyses heavily depends on the quality of raw sequencing data. Quality control (QC) and trimming are critical preprocessing steps that can make or break your downstream analyses. In this blog, we explore the "ifs" (why you should perform QC and trimming) and the "buts" (challenges or considerations) of this vital step in NGS workflows.</p><h3><strong>The "Ifs" of NGS QC and Trimming</strong></h3><ol>
<li>
<p><strong>Ensures Data Integrity</strong><br />If you want to minimize errors in downstream analyses, QC and trimming remove low-quality reads and bases, ensuring high-confidence data. This step is essential for reliable variant calling, assembly, and other applications.</p>
</li>
<li>
<p><strong>Removes Contaminants</strong><br />If adapter sequences or contaminants are present in the raw reads, trimming can eliminate them. This prevents issues like misalignment or incorrect biological interpretations, ensuring cleaner data for analysis.</p>
</li>
<li>
<p><strong>Improves Mapping and Assembly</strong><br />If your goal is better alignment to a reference genome or improved de novo assembly, trimming low-quality bases and adapters is critical. High-quality reads map more efficiently and generate more accurate assemblies.</p>
</li>
<li>
<p><strong>Reduces Computational Load</strong><br />If you want to save computational resources, trimming reduces the dataset size, which speeds up processing and analysis. Clean datasets mean less computational time spent on processing low-quality data.</p>
</li>
<li>
<p><strong>Prepares for Standardized Analyses</strong><br />If your project involves multiple datasets, QC and trimming ensure uniformity across them. This standardization makes comparisons valid and reproducible, particularly in large collaborative studies.</p>
</li>
</ol><h3><strong>The "Buts" of NGS QC and Trimming</strong></h3><ol>
<li>
<p><strong>Risk of Over-Trimming</strong><br />But excessive trimming can lead to the loss of informative sequences, reducing read depth and potentially discarding biologically relevant data. This is especially critical in studies with limited sequencing depth.</p>
</li>
<li>
<p><strong>Bias Introduction</strong><br />But trimming algorithms might introduce biases, especially if they inadvertently remove sequences with specific biological patterns. This can skew results and compromise biological insights.</p>
</li>
<li>
<p><strong>Loss of Context in Paired-End Reads</strong><br />But trimming one read in a pair more than the other can lead to loss of pairing information. This complicates downstream analyses that rely on paired-end data, such as structural variant detection.</p>
</li>
<li>
<p><strong>Time and Resource Intensive</strong><br />But running QC and trimming for large datasets can be computationally expensive and time-consuming. As sequencing depth increases, preprocessing becomes a bottleneck in the analysis pipeline.</p>
</li>
<li>
<p><strong>Variable Standards</strong><br />But the criteria for trimming (e.g., quality threshold, minimum read length) can vary between tools and datasets. This variability may affect reproducibility and comparability of results across studies.</p>
</li>
</ol><h3><strong>Balancing the "Ifs" and "Buts"</strong></h3><p>To maximize the benefits of QC and trimming while mitigating the challenges, consider the following best practices:</p><ul>
<li>
<p><strong>Use QC Tools Wisely:</strong> Start with tools like <strong>FastQC</strong> to identify quality issues in your raw data. Visualizing quality metrics helps tailor your trimming parameters.</p>
</li>
<li>
<p><strong>Choose Reliable Trimming Tools:</strong> Tools like <strong>Trimmomatic</strong>, <strong>Cutadapt</strong>, and <strong>BBduk</strong> offer adaptive and customizable trimming options. Select one that aligns with your dataset and project goals.</p>
</li>
<li>
<p><strong>Set Reasonable Parameters:</strong> Avoid over-trimming by setting quality thresholds and minimum read lengths that balance data retention and quality improvement.</p>
</li>
<li>
<p><strong>Test Downstream Effects:</strong> Validate the impact of QC and trimming on downstream analyses, such as alignment efficiency, variant calling accuracy, or assembly quality.</p>
</li>
<li>
<p><strong>Document Your Workflow:</strong> Maintain detailed records of the parameters and tools used for QC and trimming. This ensures reproducibility and enables better troubleshooting.</p>
</li>
</ul><h3><strong>Conclusion</strong></h3><p>NGS quality control and trimming are essential steps to ensure reliable and accurate data for analysis. While the "ifs" highlight the clear benefits of these steps, the "buts" remind us of the potential pitfalls. By adopting best practices and carefully balancing these considerations, you can optimize your preprocessing workflow and unlock the full potential of your sequencing data.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23379/jrf-in-bioinformatics-tezpur-universityn</guid>
  <pubDate>Fri, 17 Jul 2015 19:42:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF in Bioinformatics @ Tezpur Universityn]]></title>
  <description><![CDATA[
<p>Tezpur University: Napaam – 784 028:</p>

<p>Assam Applications are invited for Walk-in-Interview for the following temporary positions in the MHRD sponsored Centre of Excellence under FAST project entitled “Machine Learning Research and Big Data Analysis” under the Principal Investigator Professor D.K. Bhattacharyya, Department of Computer Science &amp; Engineering, Tezpur University.</p>

<p>Position : Senior Research Fellows (SRFs) in the field of (i) Bioinformatics (ii) Natural Language Processing / Speech Processing (iii) Cognitive Radio Networks / Optical Networks (iv) Network Security. No. of Positions : Five (05).</p>

<p>Qualification : First class in ME / M. Tech. in CSE / IT / ECE with research experience in relevant fields of research. Candidates having valid GATE / NET score shall be preferred.</p>

<p>Fellowship : Rs. 18,000/- (Rupees Eighteen Thousand) only per month.</p>

<p>Duration : Two (02) years and may be extended depending on status of the project.</p>

<p>Position : Junior Research Fellows (JRFs) in the field of Bioinformatics</p>

<p>No. of Positions : One (01).</p>

<p>Qualification : First class in B. Tech. in CSE / IT/ ECE or MCA with consistently good academic records. Candidates with M. Tech. in CSE / IT / ECE shall be preferred.</p>

<p>Fellowship : Rs. 12,000/- (Rupees twelve Thousand) only per month.</p>

<p>Duration : Two (02) years and may be extended depending on status of the project.</p>

<p>Interested candidates may send their application on plain paper by post along with his/her educational qualifications, research experience certificates (for Senior Research Fellow), 02 copies of recent passport/stamp size photograph and contact phone number to Prof. D.K. Bhattacharyya, Principal Investigator, Department of Computer Science &amp; Engineering, Tezpur University, Napaam- 784028 or mail it to dkb@tezu.ernet.in (or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.</p>

<p>Advertisement: www.tezu.ernet.in/ProjectWalkin/Advt_CoE_5816-A.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</guid>
	<pubDate>Thu, 04 Oct 2018 16:30:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules</link>
	<title><![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]></title>
	<description><![CDATA[<p>VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.</p>
<h5>&nbsp;</h5><p>Address of the bookmark: <a href="https://github.com/broadinstitute/VariantBam" rel="nofollow">https://github.com/broadinstitute/VariantBam</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23493/srf-post-in-nehu-shillong</guid>
  <pubDate>Sat, 25 Jul 2015 20:09:50 -0500</pubDate>
  <link></link>
  <title><![CDATA[SRF post in NEHU, Shillong]]></title>
  <description><![CDATA[
<p>Dept of Biochemistry<br />North-Eastern Hill University<br />Umshing, Shillong- 793 022</p>

<p>Applications are invited for the post of Senior Research Fellow- SRF (one) and Junior Research Fellow- JRF (one) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong.</p>

<p>Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite.</p>

<p>For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by publications.</p>

<p>Students waiting for their last semester result can apply for JRF position.</p>

<p>Stipend: As per SERB norms.</p>

<p>Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 01.08.15. The hard copy is not required at this stage.</p>

<p>The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. P.S: Students applied for the same post as per date 01.06.15, need not to apply again as their application will be considered in this advertisement also.</p>

<p>For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com</p>

<p>Dr. Timir Tripathi Principal Investigator DST-SERB Project Department of Biochemistry NEHU, Shillong</p>

<p>Advertisement: www.nehu.ac.in/Advertisements/BiochemPVAdvtTT_200715.pdf</p>
]]></description>
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