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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/10749?offset=1180</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</guid>
	<pubDate>Mon, 25 Aug 2014 01:26:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers</link>
	<title><![CDATA[Apps for Busy Bioinformatics Researchers !!!]]></title>
	<description><![CDATA[<h3>DNAApp:</h3><h4><strong>DNAApp: for </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank"><strong>iPhone/iPad</strong></a></h4><p>This is an <a href="http://www.apple.com/ios/" target="_blank" title="IOS">iOS</a> app that allows for the opening and analysis of <a href="http://en.wikipedia.org/wiki/DNA_sequencing" target="_blank" title="DNA sequencing">DNA sequencing</a> files - ab1. It includes handy tools such as "<a href="http://en.wikipedia.org/wiki/Complementarity_%28molecular_biology%29" target="_blank" title="Complementarity (molecular biology)">Reverse Complement</a>", "Jump to", "<a href="http://en.wikipedia.org/wiki/Cut%2C_copy%2C_and_paste" target="_blank" title="Cut, copy, and paste">Copy and Paste</a> sequences", fast and end scrolling, "<a href="http://en.wikipedia.org/wiki/Chromatography" target="_blank" title="Chromatography">Chromatogram</a> adjustments", and "Searching for segments" functions. <br /> When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files. <br /> This app works with cloud storage access like Dropbox to your sequencing files. <br /> This is now compatible with the new update for iOS 7.1. <br /> Demo video can be found at:<strong> https://www.youtube.com/watch?v=mXeo9hXdZgM&nbsp;</strong></p><p><strong>More @ </strong><a href="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8" target="_blank" title="https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8"><strong>https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8</strong></a></p><h4><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank"><strong>DNAApp: For android</strong></a></h4><p>This is the first android app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", fast and end scrolling, "Chromatogram adjustments", amino acid translations, "export to fasta", and "searching for segment" function.</p><ul>
<li>When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.</li>
<li>This app works with cloud storage access like Dropbox to your sequencing files.</li>
<li>This is now compatible with the new update for <a href="http://code.google.com/android/" target="_blank" title="Android">Android</a> 4.4.2.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=bii.seqdatreader&amp;hl=en</strong></a></p><h3>BioGene:iPhone/iPad</h3><p>BioGene is an information tool for biological research. Use BioGene to learn about gene function. Enter a gene symbol or gene name, for example "CDK4" or "cyclin dependent kinase 4" and BioGene will retrieve its gene function and references into its function (<a href="http://en.wikipedia.org/wiki/GeneRIF" target="_blank" title="GeneRIF">GeneRIF</a>).</p><ul>
<li>BioGene was produced in affiliation with the Computational Biology Center at <a href="http://maps.google.com/maps?ll=40.764096,-73.956842&amp;spn=0.01,0.01&amp;q=40.764096,-73.956842%20%28Memorial%20Sloan%E2%80%93Kettering%20Cancer%20Center%29&amp;t=h" target="_blank" title="Memorial Sloan&ndash;Kettering Cancer Center">Memorial Sloan-Kettering Cancer Center</a> with primary information from Entrez Gene at the <a href="http://maps.google.com/maps?ll=38.994994,-77.099339&amp;spn=0.01,0.01&amp;q=38.994994,-77.099339%20%28National%20Center%20for%20Biotechnology%20Information%29&amp;t=h" target="_blank" title="National Center for Biotechnology Information">NCBI</a>.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/biogene/id333180084?mt=8" target="_blank" title="https://itunes.apple.com/us/app/biogene/id333180084?mt=8"><strong>https://itunes.apple.com/us/app/biogene/id333180084?mt=8</strong></a></p><h3>Mentha - the interactome browser: Android</h3><p>About: mentha - the interactome browser, is a project that offers protein-protein physical/enzymatic interaction information from various sources. For more details about mentha, visit mentha's website. This client application is an independent project. This application is designed to allow you to search proteins on the go.</p><h4><strong>Key features (Also in website):</strong></h4><ul>
<li>Search proteins by <a href="http://en.wikipedia.org/wiki/UniProt" target="_blank" title="UniProt">UniProt</a> IDs, gene name or keywords</li>
<li>Collect proteins from different queries.</li>
<li>Spot common interactors in clusters.</li>
<li>Easily distinguish between proteins from Homo sapiens and other organisms (Yellow rounded rectangles)</li>
<li>Click on edges(links) to get scientific evidence.</li>
<li>Click on proteins to see descriptions.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en"><strong>https://play.google.com/store/apps/details?id=com.sinnefa.mentha&amp;hl=en</strong></a></p><h3>GeneIndex: iPhone/iPad</h3><p>GeneIndex quickly provides information about genes from various sources. It also includes a RSS reader for journal feeds as well as a PubMed viewer.</p><h4><strong>Key Features:</strong></h4><ul>
<li>Look up genes by symbol or description.</li>
<li>Gene indexes for many mammals, plants, invertebrates, and bacteria.</li>
<li>Link to gene info on websites.</li>
<li>Download files for offline use. (.pdf, .mp3, .m4v, .doc, .ppt, .xls )</li>
<li>transfer files via open in, email, or iTunes file sharing</li>
<li>View RSS feeds for journals</li>
<li>Query GeneRIF interactions, COSMIC mutations, and CNV data for cell lines.</li>
<li>Does not require a network connection for local databases.</li>
<li>View and search PubMed in table view.</li>
</ul><p><br /> GeneIndex provides a convenient and portable way to lookup gene symbols while at a seminar, conference, or lab meeting. Genes are linked to common life science websites such as NCBI, COSMIC, KEGG, PubMed, SymAtlas, UCSC genome browser, Pathway Commons, Genatlas, Wikipedia, HUGO, and OMIM. GeneRIF gene interactions can also be queried.</p><ul>
<li>Keep current on the scientific literature. GeneIndex includes a RSS reader and web browser for browsing popular journals like Nature, Science, and Cell. You can also add your own RSS feeds. PDFs and podcasts can be saved as files that you can view on the device or email as attachments.</li>
<li>Examine the status of genes in common cell lines. A subset of COSMIC containing cell lines can be queried for mutations. Copy Number Variation (CNV) plots from cell lines profiled by GSK and Sanger are also linked to genes.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8" target="_blank" title="https://itunes.apple.com/us/app/geneindex/id319769866?mt=8"><strong>https://itunes.apple.com/us/app/geneindex/id319769866?mt=8</strong></a></p><h3>Genome Voyager: iPad</h3><p>Gain first hand experience identifying the genomic basis of disease by analyzing cases with whole genome sequencing data that have been published for research and learning purposes.</p><ul>
<li>Visualize whole human genome sequencing data including small variations, copy number variations (CNVs), and loss of heterozygosity (LOH) events</li>
<li>Quickly find variants of interest by filtering variants based on associated genes, functional impact, allele frequency in data sets, and cross-references with various genomic databases.</li>
<li>Collaborate on variant assessments with other researchers and academics to improve knowledge of both pathogenic and benign variants. <br /> To use Genome Voyager, users must join Genome Voyager&rsquo;s community of researchers and academics. Visit <strong>http://voyager.completegenomics.com to signup.</strong></li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8"><strong>https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8</strong></a></p><h3>YeastGenome: iPhone/iPad</h3><p>Use YeastGenome to quickly find fundamental information about Saccharomyces cerevisae genes and chromosomal features. Search gene names, gene descriptions or browse the database to find information about your favorite gene, as well as more detailed information such as Gene Ontology, mutant phenotype, and protein and genetic interaction data. <br /> YeastGenome contains the latest from the Saccharomyces Genome Database (www.yeastgenome.org) in an on bound app database. As more detailed information is presented the app switches to web services access to SGD, and then for even more details provides complete information via hyperlinks to the appropriate SGD database pages.</p><h4><strong>Key features:</strong></h4><ul>
<li>Search using gene name or keywords</li>
<li>Browse by feature type</li>
<li>Save your favorite features</li>
<li>Can be used in airplane mode</li>
<li>Email information about features to collaborators</li>
</ul><h4><strong>What's New in Version 1.8.1</strong></h4><ul>
<li>This update is required to provide continued functionality. Some of the data provided by this app accesses the SGD service using a method that is changing in May 2013. This version provides changes to allow access to continue. The on board database of yeast gene information has also been updated to March 2013.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8" target="_blank" title="https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8"><strong>https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8</strong></a></p><h3>SNPdbe: iPhone/iPad</h3><p>SNPdbe &mdash; SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from &gt;2600 organisms; &lsquo;human&rsquo; being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8" target="_blank" title="https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8"><strong>https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8</strong></a></p><h3>SimGene: iPhone/iPad / Android</h3><h4><strong>SimGene: for iPhone/iPad </strong></h4><p>SimGene is an iPhone/iPad/iPod touch application designed for molecular biologists, bioinformaticians and medical researchers. The application interfaces with Simbiot, Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations and many other databases to retrieve up-to-date annotation information for over 30 species, based on gene symbol search. The application provides gene and transcript cross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene also contains an integrated genome browser with information on genes, transcripts, exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/simgene/id427772349?mt=8" target="_blank" title="https://itunes.apple.com/us/app/simgene/id427772349?mt=8"><strong>https://itunes.apple.com/us/app/simgene/id427772349?mt=8</strong></a></p><h4><strong>SimGene: for Android</strong></h4><p>bioinformaticians and medical researchers. The application interfaces with Simbiot,Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations andmany other databases to retrieve up-to-date annotation information for over 30species, based on gene symbol search. The application provides gene and transcriptcross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene alsocontains an integrated genome browser with information on genes, transcripts,exons and SNPs.</p><p><strong>More @&nbsp; </strong><a href="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en" target="_blank" title="https://play.google.com/store/apps/details?id=com.japanbioinformatics.simgene&amp;hl=en"><strong>https://play.google.com/store/apps/details?</strong></a></p><h3>TimeTree: iPhone/iPad</h3><p>TimeTree is a public knowledge-base for information on the evolutionary timescale of life. This application allows easy exploration of the thousands of divergence times among organisms in the scientific literature. A tree-based (hierarchical) system is used to identify all published molecular time estimates bearing on the divergence of two chosen organisms, such as species, compute summary statistics, and present the results. Names of two taxa to be compared are entered in the search window and the results are presented on a set of self-explanatory tabs.</p><ul>
<li>TimeTree 3.0 was released September 27, 2011 with new data from 1209 studies including 25342 time nodes. We will be adding more data in the future as it comes in from researchers.</li>
<li>TimeTree is jointly directed by Blair Hedges (Pennsylvania State University) and Sudhir Kumar (Arizona State University). This project has been supported, in part, by grants from the National Science Foundation, National Institutes of Health, NASA Astrobiology Institute, and Science Foundation of Arizona.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/timetree/id372842500?mt=8" target="_blank" title="https://itunes.apple.com/us/app/timetree/id372842500?mt=8"><strong>https://itunes.apple.com/us/app/timetree/id372842500?mt=8</strong></a></p><h3><strong>GeneGroove: iPhone/iPad </strong></h3><p>GeneGroove is the first application to create a music melody from DTC-Genomics data. If you own 23andMe (Mountain View, CA) personal genomic results, GeneGroove will create for you a unique melody intimately based on your 23andMe genome informations. The music in you.</p><ul>
<li>After uploading your 23andMe raw data onto your iPhone via iTunes, GeneGroove will analyze your genome informations and generate a unique identifier key. This key, called the GeNumber, will embed the uniqueness of your genome data while keeping your privacy safe, and will be used by GeneGroove to generate your music melody.</li>
<li>The GeNumber doesn't contain anymore genomic information but it is based on your genome and it is unique, it is yours. It will be used in upcoming Portable Genomics applications to mix and remix music, manipulate sounds and share your art with your friends and family.</li>
</ul><p><strong>More @&nbsp; </strong><a href="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8" target="_blank" title="https://itunes.apple.com/us/app/genegroove/id492247404?mt=8"><strong>https://itunes.apple.com/us/app/genegroove/id492247404?mt=8</strong></a></p>]]></description>
	<dc:creator>Manisha Mishra</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</guid>
	<pubDate>Wed, 22 Aug 2018 22:10:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/37581/comparativegenomics-exercise2</link>
	<title><![CDATA[ComparativeGenomics Exercise2]]></title>
	<description><![CDATA[<p>COMPARATIVE MICROBIAL GENOMICS ANALYSIS WORKSHOP&nbsp; @&nbsp;cbs.dtu.dk</p><p>Free Bioinformatics workbench https://www.mn.uio.no/ifi/english/research/networks/clsi/earlier_seminars/2012/tammivesth_osloseminarfinal.pdf</p>]]></description>
	<dc:creator>Neel</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/37581" length="139956" type="application/pdf" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42137/plant-computational-genomics-lab-%E2%80%93-jill-wegrzyn</guid>
  <pubDate>Thu, 20 Aug 2020 19:49:12 -0500</pubDate>
  <link></link>
  <title><![CDATA[PLANT COMPUTATIONAL GENOMICS LAB – JILL WEGRZYN]]></title>
  <description><![CDATA[
<p>Our research focuses on the computational analysis of genomic and transcriptomic sequences from non-model plant species. We do this by developing approaches to examine gene finding, gene expression, transcriptome assembly, and conserved element identification, through machine learning and computational statistics. We use these novel methods to address questions related to genome biology and population genomics.</p>

<p>We also develop web-based applications that integrate data across domains to facilitate the forest geneticist or ecologist’s ability to analyze, share, and visualize their data. Such integration requires the implementation of semantic technologies and ontologies to connect genotype, phenotype, and environmental data.</p>

<p>http://plantcompgenomics.com/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42712/scientist-c-non-medical-it-expert-computer-professionalgenomicsbioinformatic-at-nimr</guid>
  <pubDate>Mon, 01 Feb 2021 13:54:06 -0600</pubDate>
  <link></link>
  <title><![CDATA[Scientist C - Non-Medical (IT Expert- Computer Professional/Genomics/Bioinformatic) at NIMR]]></title>
  <description><![CDATA[
<p>Applications are invited upto 12th February 2021 in the prescribed format (available on the websites of ICMR-NIMR) through link http://onlineapply.nimr.org.in/ up to 05:00 PM on 12th February 2021 for the following post on contract basis at NIMR, Sector-8, Dwarka, New Delhi.</p>

<p>Scientist C - Non-Medical (IT Expert- Computer Professional/Genomics/Bioinformatic)No. of posts: 01 (UR)</p>

<p>Salary (Fixed): Rs.51,000/- + HRA</p>

<p>Essential Qualification: Candidate should possess 1st class master degree in relevant subjects from a recognized university with 4 years experience<br />OR<br />2nd class M.Sc + Ph.D degree in relevant subjects from a recognized university with 4 years experience.Desirable Qualification: Candidates should possess a PhD degree in any field of science.<br />Preference will be given to those who have published scientific papers in international journals and who have a track record of working in infectious diseases.</p>

<p>The candidate must know the following for further consideration: (a) data processing and analysis using statistical softwares, (d) programming, (e) presentation of complex data from excel files and related skills.<br />Understanding of GIS and malaria will be an advantage. Experience and interest in functional genomics and genomic sequencing will be important.</p>

<p>Age Limit: 40 YearsDuration: 30.09.2021</p>

<p>More at http://onlineapply.nimr.org.in/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/16313/project-assistant-position-at-jmi</guid>
  <pubDate>Fri, 12 Sep 2014 00:37:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[Project Assistant Position at JMI]]></title>
  <description><![CDATA[
<p>Project Assistant Position (@ Rs.10,000/pm Fixed) is available for one year ina research project funded by the Department of Science and Technology entitled, "Folding and stability of naturally truncated photosynthetic pigment,C- phycoerythrin from cyanobacterium Phormidium tenue", at Centre forInterdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025 under' the supervision of Dr. Md. Imtaiyaz Hassan (PrincipalInvestigator).</p>

<p>Eligibility:<br />M.Sc. in any stream of Life Sciences with minimum 55% marks.</p>

<p>Desirable:<br />Candidates having experience in Molecular Spectroscopy, Protein Folding and Bioinformatics will be preferred.</p>

<p>Interested candidate may appear in the walk in Interview conducted on September 16, 2014 (Tuesday) 11:00 AM in the Director's Office, Centre for Interdisciplinary Research in Basic Sciences, lamia Millia Islamia, New Delhi-110025.<br />Candidates are required to bring a set of Xerox copy of their recent CV and qualifying degree (certificate/mark sheet) along with original documents. NoTA/DA will be paid.</p>

<p>For any further information you may e-mail to: mihassan@jmLac.in</p>

<p>Read more at http://jmi.ac.in/upload/advertisement/jobs_cirbs_2014september8.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44395/genomics-india-conference-2024</guid>
  <pubDate>Fri, 27 Oct 2023 05:48:11 -0500</pubDate>
  <link></link>
  <title><![CDATA[Genomics India Conference 2024 !]]></title>
  <description><![CDATA[
<p>Genomics India Conference is back and this time we are coming to Shiv<br />Nadar Intitution of Eminenece, Delhi NCR. GIC 2024 will be held from 1st<br />to 3rd of February 2024 and we are happy to send you an early invitation<br />for India's premier genomics conference.</p>

<p>GIC2024 focuses on "Advances In Genomics From AI-ML To Targeted<br />Therapies". GIC2024 encourages researchers to present original<br />contributions for poster presentations.</p>

<p>Note: Early bird registration closes on 1st December 2023.</p>

<p>Kindly, register at GIC 2024 Earlybird registartion</p>

<p>https://genomicsindia.co.in/</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/17188/jamia-hamdard-bioinformatics-faculty-jobs-2014</guid>
  <pubDate>Sat, 20 Sep 2014 21:00:05 -0500</pubDate>
  <link></link>
  <title><![CDATA[JAMIA HAMDARD Bioinformatics Faculty Jobs 2014]]></title>
  <description><![CDATA[
<p>JAMIA HAMDARD</p>

<p>(Deemed University)</p>

<p>Hamdard Nagar, New Delhi – 110 062</p>

<p>R E C R U I T M E N T</p>

<p>(Advertisement No. 5/2014)</p>

<p>Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.</p>

<p>1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000</p>

<p>2. Assistant Professor                   -  Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-</p>

<p>ASSISTANT PROFESSOR – 02 (including 01 SFS)</p>

<p>Specialization : Bioinformatics</p>

<p>Qualification and Experience :</p>

<p>Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.</p>

<p>NET in Life Science or allied discipline in addition to the above qualification.</p>

<p>Experience : At  least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University.  Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.</p>

<p>Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.</p>

<p>For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf<br />http://www.jamiahamdard.ac.in/PDF/PBAS.pdf</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/researchlabs/view/17500/joao-pedro-de-magalhaes-lab</guid>
  <pubDate>Fri, 26 Sep 2014 19:08:34 -0500</pubDate>
  <link></link>
  <title><![CDATA[Joao Pedro de Magalhaes Lab]]></title>
  <description><![CDATA[
<p>Ageing has a profound impact on human society and modern medicine, yet it remains a major puzzle of biology. The goal of my work is to help understand the genetic, cellular, and molecular mechanisms of ageing. In the long term, I would like my work to help ameliorate age-related diseases and preserve health. No other biomedical field has so much potential to improve human health as research on the basic mechanisms of ageing. Please see our lab website for further details about our work and publications. </p>

<p>Functional and Comparative Genomics</p>

<p>http://jp.senescence.info/<br />http://www.senescence.info/<br />http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/</p>
]]></description>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</guid>
	<pubDate>Wed, 11 Feb 2015 04:59:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/21150/webinar-on-an-integrated-rna-and-dna-approach-to-unravel-genetic-regulation-in-cancer</link>
	<title><![CDATA[Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer']]></title>
	<description><![CDATA[<div><p><strong>Webinar on 'An integrated RNA and DNA approach to unravel genetic regulation in cancer'</strong></p><p><strong>Abstract</strong></p><p>Whole exome DNA sequencing (WES) or whole genome DNA sequencing (WGS) allows detection of mutations and polymorphisms in all exonic and genomic regions, respectively, while messenger RNA sequencing (RNA-Seq) enables quantitative analysis of gene expression. Mutations in the genome result in diverse transcriptional aberrations that can be missed in a stand-alone WES/WGS analysis. An integration of DNA variant analysis and RNA-Seq analysis enables one to investigate the consequences of genomic changes in the RNA transcripts including germline and somatic changes, imprinting, RNA editing and allele specific expression (ASE). In this webinar, we will demonstrate this integrated approach using Strand NGS to identify high confidence mutations, RNA editing events and ASE in cancer.</p><p><strong>Webinar Details</strong></p><table width="100%" border="1" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="top">
<p style="text-align: center;"><br /> <strong>Sessions</strong></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>San Francisco Time<br /> (PST)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Tokyo Time<br /> (GMT+09:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Berlin Time<br /> (GMT+01:00)</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Mumbai Time<br /> (GMT+05:30)</strong></a></p>
</td>
</tr>
<tr>
<td>
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 1</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 12:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 5:30 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:30 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 2:00 PM</p>
</td>
</tr>
<tr>
<td valign="top">
<p style="text-align: center;"><a href="http://www.strand-ngs.com/webinar_registration"><strong>Session 2</strong></a></p>
</td>
<td valign="top">
<p style="text-align: center;">25 Feb&nbsp;<br /> 9:00 AM</p>
</td>
<td>
<p style="text-align: center;">26 Feb<br /> 2:00 AM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 6:00 PM</p>
</td>
<td>
<p style="text-align: center;">25 Feb&nbsp;<br /> 10:30 PM</p>
</td>
</tr>
</tbody>
</table><p><strong style="font-size: 12.8000001907349px;">Register here: </strong><a href="http://www.strand-ngs.com/webinar_registration">http://www.strand-ngs.com/webinar_registration</a></p><p><strong>About Speaker:</strong></p><p>Dr. Veena Hedatale, has a PhD in Plant Genetics from The Radboud University, Netherlands focused on meiosis and recombination. Her prior academic experience at Cornell University was on genetic mapping and gene transformation in Rice. She has worked with Monsanto, and contributed to data mining, database development as well as gene/promoter/pathway discovery for traits related to yield and stress in crop species. At Strand, Veena has worked on Pharmacogenomic analysis of targets and Gene family analysis projects. Currently, she is part of the Strand NGS Application Science team and is involved in the analysis of next generation sequencing data.</p><p>Please feel free to contact us 24/5, for availing free online training or if you have any questions.</p></div><div><p><strong style="font-size: 12.8000001907349px;">Email:</strong> sales@strandngs.com</p><p><strong>Phone (USA):</strong> 1-800-752-9122</p><p><strong>Phone (ROW):</strong> +1-650-353-5060</p><p>&nbsp;</p></div>]]></description>
	<dc:creator>Yeshodari</dc:creator>
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