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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29382?offset=1010</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20672/jrfra-structuralcomputational-biology-at-icgeb</guid>
  <pubDate>Thu, 29 Jan 2015 11:52:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[JRF/RA Structural/Computational Biology at ICGEB]]></title>
  <description><![CDATA[
<p>Research Associate and JRF positions in the Structural and Computational Biology Group starting 1st March 2015. Collaborative projects include work on:</p>

<p>a) bioinformatics, systems and computational biology <br />b) malaria <br />c) drug discovery <br />d) genomics <br />e) microbiology <br />f) metabolic disorders <br />g) molecular medicine</p>

<p>Eligibility: Applicants must have one of the following :</p>

<p>1) INSPIRE award for undertakig either PhD or Postdoctoral research; <br />2) SPM award for PhD; <br />3) JRF for pursuing PhD from CSIR/DBT/ICMR</p>

<p>Interest and experience in Biochemistry/Bioinformatics/Biophysics/ Chemistry/Genomics/Molecular Biology/ is essential.</p>

<p>Submit curriculum vitae to sb.icgeb@gmail.com by 20 February 2015</p>
]]></description>
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	<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/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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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</guid>
	<pubDate>Tue, 11 Sep 2018 04:44:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37674/qualimap2-evaluating-next-generation-sequencing-alignment-data</link>
	<title><![CDATA[Qualimap2: Evaluating next generation sequencing alignment data]]></title>
	<description><![CDATA[<p><strong>Qualimap 2</strong><span>&nbsp;is a platform-independent application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.&nbsp;</span><br><br><span>Supported types of experiments include:</span></p>
<ul>
<li>Whole-genome sequencing</li>
<li>Whole-exome sequencing</li>
<li>RNA-seq (speical mode available)</li>
<li>ChIP-seq</li>
</ul><p>Address of the bookmark: <a href="http://qualimap.bioinfo.cipf.es/" rel="nofollow">http://qualimap.bioinfo.cipf.es/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/20959/research-associate-and-jrf-positions-in-the-structural-and-computational-biology-group-at-icgeb</guid>
  <pubDate>Mon, 02 Feb 2015 23:00:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[Research Associate and JRF positions in the Structural and Computational Biology Group at ICGEB]]></title>
  <description><![CDATA[
<p>Research Associate and JRF positions in the Structural and Computational Biology Group starting 1st March 2015. Collaborative projects include work on:</p>

<p>a) bioinformatics, systems and computational biology <br />b) malaria <br />c) drug discovery <br />d) genomics <br />e) microbiology <br />f) metabolic disorders <br />g) molecular medicine</p>

<p>Eligibility: Applicants must have one of the following :</p>

<p>1) INSPIRE award for undertakig either PhD or Postdoctoral research; <br />2) SPM award for PhD; <br />3) JRF for pursuing PhD from CSIR/DBT/ICMR</p>

<p>Interest and experience in Biochemistry/Bioinformatics/Biophysics/ Chemistry/Genomics/Molecular Biology/ is essential.</p>

<p>Submit curriculum vitae to sb.icgeb@gmail.com by 20 February 2015</p>
]]></description>
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	<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/opportunity/view/21065/ra-bioinformatics-at-north-eastern-hill-university</guid>
  <pubDate>Sat, 07 Feb 2015 06:06:05 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at North Eastern Hill University]]></title>
  <description><![CDATA[
<p>Bioinformatics Infrastructure Facility, Department of RDAP, NEHU vacancy of Research Associate</p>

<p>Name of the Post: Research Associate<br />No. of the Post: 01 One<br />Age Limit: Max. 35 years<br />Salary: Rs. 22000/- per month plus HRA</p>

<p>Required Job Profile:<br />Candidate must possess M.Sc. in bioinformatics or biotechnology from recognized university or institute.<br />Desired Job Profile;<br />Candidate having Ph.D. or pursuing Ph.D. in the related subject or equivalent published work in reputed peer reviewed journals or advance PG dipoma in bioinformatics course.</p>

<p>How to apply:<br />Eligible and interested candidates should need to send the bio-data and bring all related documents in original and set of attested copies of the same in the time of interview.</p>

<p>Last date: 16.02.2015<br />Refer to http://www.nehu.ac.in/Advertisements/BIFTuraAdvt_221214.pdf</p>

<p>Summary <br />Employer Address:	Dr.B.K. Mishra Coordinator BIF, RDAP Department, North Eastern Hill University, Tura Campus, Tura, Meghalaya<br />Email:	drbkm1972@yahoo.co.in;birendramishra14@gmail.com<br />URL:	http://www.nehu.ac.in/Advertisements/BIFTuraAdvt_221214.pdf<br />Phone:	03651-223107<br />Required Skills:	not mentioned / required for this post<br />Required Experience:	not mentioned / required for this job post<br />Required Education:	M.Sc. in bioinformatics or biotechnology from recognized university or institute.<br />Job Location:	Tura, Meghalaya, India</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41009/genomics-public-data-links</guid>
	<pubDate>Thu, 13 Feb 2020 00:20:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41009/genomics-public-data-links</link>
	<title><![CDATA[genomics public data links !]]></title>
	<description><![CDATA[<p>List of publically available databases on google server.</p>
<p>More at <a href="https://software.broadinstitute.org/gatk/download/bundle">https://software.broadinstitute.org/gatk/download/bundle</a></p>
<p><a href="ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/">ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/</a>.</p>
<p><a href="ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/">ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/</a></p><p>Address of the bookmark: <a href="https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1" rel="nofollow">https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21241/pacman</guid>
	<pubDate>Mon, 16 Feb 2015 12:15:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21241/pacman</link>
	<title><![CDATA[Pacman]]></title>
	<description><![CDATA[<p><span>The pacman package is an R package management tool that combines the functionality of base library related functions into intuitively named functions. This package is ideally added to .Rprofile to increase workflow by reducing time recalling obscurely named functions, reducing code and integrating functionality of base functions to simultaneously perform multiple actions.<br /><br />Function names in the pacman package follow the format of p_xxx where &lsquo;xxx&rsquo; is the task the function performs. For instance the p_load function allows the user to load one or more packages as a more generic substitute for the library or require functions and if the package isn&rsquo;t available locally it will install it for you.<br /><br /></span></p><p><strong>Installation</strong></p><p><span>To download the development version of pacman:</span></p><p><span>Download the </span><a href="https://github.com/trinker/pacman/zipball/master">zip ball</a><span> or </span><a href="https://github.com/trinker/pacman/tarball/master">tar ball</a><span>, decompress and run </span><code>R CMD INSTALL</code><span> on it, or use th</span><span>e </span><strong>devtools</strong><span> package to install the development version:</span></p><pre title="">## Make sure your current packages are up to date
update.packages()
## devtools is required
devtools::install_github("trinker/pacman")
</pre><p>Note: Windows users need <a href="http://www.murdoch-sutherland.com/Rtools/">Rtools</a> and <a href="http://CRAN.R-project.org/package=devtools">devtools</a> to install this way.</p><p>More at https://github.com/trinker/pacman</p><p>&nbsp;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/21435/ra-walk-in-interview-nbfgr-lucknow</guid>
  <pubDate>Tue, 24 Feb 2015 08:23:48 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA WALK-IN-INTERVIEW @ NBFGR, Lucknow]]></title>
  <description><![CDATA[
<p>F.No. 1(122)/2015-Admn. (CABin Project)<br />Research Associate/Young Professional/SRF Zoology job vacancies in National Bureau of Fish Genetic Resources (NBFGR)<br />Post Name: Research Associate (Computer Science/ Applications)                <br />Qualification: Ph.D. In Computer Science/Computer Applications or equivalent. Or Post-Graduation in Computer Science/ Computer Applications with 1st Division or 60% marks or equivalent overall grade point average with at least two years of research experience. Desirable: 1. Expertise and experience of working/ handling High Performance Computing (H PC) and genomic resource data. 2. Expertise on database management, data mining technologies/ softwares/tools. 3. Published Research papers	<br />No.of Post: 1<br />Pay Scale: Consolidated Rs.24,000/- p.m. + HRA (as admissible) for Ph.D. holders and consolidated `23,000/- + HRA (as admissible) for Master degree holder.	<br />Age:40 years</p>

<p>Young Professional II (Computer Science/Applications)	<br />Master degree in Computer Science/Computer Applications/B.Tech (Computer Science) or equivalent. <br />Desirable: 1. Knowledge of Statistical and Computational Genomics/ Proteomics/ Bioinformatics/Data mining tools. 2. Experience in handling HPC, programming languages and database management packages.	<br />A consolidated salary of Rs.25,000/- per month.	<br />21 to 45 year</p>

<p>Young Professional II (Biotechnology/ Bioinformatics)	<br />Master degree in Bioinformatics/ Biotechnology/ B. Tech(Biotech) or equivalent. Desirable: 1. Knowledge of Computational Genomics/Proteomics/Bioinformatics. 2. Expertise in NGS data analysis and knowledge of allied software and tools.	<br />A consolidated salary of Rs.25,000/- per month.	</p>

<p>Senior Research Fellow	<br />1. Bachelors degree with Zoology, Fisheries and 2. Master's degree in Fishery science/ Zoology with Fisheries/ Biotechnology/ Life Sciences with specialization in Fisheries/ Molecular Biology. 3. 1 st Division or 60% marks or equivalent overall grade point average. <br />Desirable: Work experience in Fisheries, molecular research techniques, bioinformatics and Computer skills. NET qualified <br />Note: The project involves extensive exploration tours and sampling from water bodies all over India	<br />Rs.16,000/- p.m. for 1st &amp; 2nd year and `18,000/- p.m. for 3rd and subsequent years +HRA (as per rules)	35 years for male and 40 years for female candidate</p>

<p>How to apply</p>

<p>A walk-in-interview will be held on 04th March, 2015 at 10:00 hrs at National Bureau of Fish Genetic Resources, Lucknow. Eligible and desirous candidates fulfilling all the requirements may appear for the interview with duly filled in application giving full details of academic records and experience(s) along with attested photocopy as well as original copy of the relevant documents and a passport size photograph on the attached proforma.</p>

<p>http://www.nbfgr.res.in/</p>
]]></description>
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