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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40699?offset=210</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/1720/postdoctoral-associate-bioinformatics-at-duke-university-medical-center</guid>
  <pubDate>Sat, 10 Aug 2013 18:38:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Associate - Bioinformatics  at Duke University Medical Center]]></title>
  <description><![CDATA[
<p>The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.</p>

<p>Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.</p>

<p>This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.</p>

<p>For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.</p>

<p>For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf</p>

<p>Duke University is an Equal Opportunity/Affirmative Action Employer.</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</guid>
	<pubDate>Tue, 12 Nov 2013 21:02:27 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/6302/a-allele-of-slc24a5-gene-is-found-to-be-responsible-for-variation-in-skin-color-of-south-east-asians-and-europeans</link>
	<title><![CDATA[A-allele of SLC24A5 gene is found to be responsible for variation in skin color of South-East Asians and Europeans]]></title>
	<description><![CDATA[<p><strong>Key finding</strong>:</p><ol>
<li><span>rs1426654 SNP of <em>SLC24A5</em>&nbsp;gene is decider of skin pigmentation variation in South Asia</span></li>
<li><span><span>rs1426654-A allele is widely spread throughout the Indian subcontinent&nbsp;</span></span></li>
<li><span>Skin pigmentation is also account by the combination of processes like selection and demographic history of populations affected by their language and origin</span></li>
<li><span><span>Sign of positive selection in Europeans, Middle East, Pakistan, Central Asia and North India but not in South India</span></span></li>
<li><span><span>In European , A-allele is almost reached to fixation</span></span></li>
</ol><p><span><span><strong>Paper</strong>:</span></span></p><p><span><span><a href="http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912">http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912</a></span></span></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</guid>
	<pubDate>Thu, 19 Apr 2018 08:06:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data</link>
	<title><![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]></title>
	<description><![CDATA[<p><span>Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from&nbsp;</span><a href="https://github.com/meiji-bioinf/heap">https://github.com/meiji-bioinf/heap</a><span>&nbsp;and our web site (</span><a href="http://bioinf.mind.meiji.ac.jp/lab/en/tools.html">http://bioinf.mind.meiji.ac.jp/lab/en/tools.html</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/meiji-bioinf/heap" rel="nofollow">https://github.com/meiji-bioinf/heap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40705/malva-genotyping-by-mapping-free-allele-detection-of-known-variants</guid>
	<pubDate>Tue, 28 Jan 2020 03:39:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40705/malva-genotyping-by-mapping-free-allele-detection-of-known-variants</link>
	<title><![CDATA[MALVA: Genotyping by Mapping-free ALlele Detection of Known VAriants]]></title>
	<description><![CDATA[<p id="p0010">MALVA is able to genotype multi-allelic SNPs and indels without mapping reads</p>
<p id="p0015">MALVA calls correctly more indels than the most widely adopted genotyping pipelines</p>
<p id="p0020">Mapping-free approaches are as accurate as alignment-based ones, while being faster</p>
<p>More at&nbsp;<a href="https://www.sciencedirect.com/science/article/pii/S2589004219302366">https://www.sciencedirect.com/science/article/pii/S2589004219302366</a></p>
<p><a href="https://www.sciencedirect.com/science/article/pii/S2589004219302366">https://www.sciencedirect.com/science/article/pii/S2589004219302366</a></p><p>Address of the bookmark: <a href="https://github.com/AlgoLab/malva" rel="nofollow">https://github.com/AlgoLab/malva</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</guid>
	<pubDate>Sun, 27 Jul 2014 20:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/13226/you-and-your-friend-have-similar-dna</link>
	<title><![CDATA[You and your friend have similar DNA !!!]]></title>
	<description><![CDATA[<p>New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS&nbsp;http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.</p><div style="text-align: center;"><img src="http://i.kinja-img.com/gawker-media/image/upload/s--CwLwHa43--/18fbmlokxcmqcjpg.jpg" alt="image" width="300" height="271" style="border: 0px; border: 0px;"></div><p>Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes &mdash; a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.&nbsp;</p><p>The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.</p><p>Reference:</p><p>http://www.pnas.org/content/111/Supplement_3/10796.full</p><p>Image : http://i.kinja-img.com</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43607/classification-of-sars-cov2-variant</guid>
	<pubDate>Fri, 26 Nov 2021 12:53:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43607/classification-of-sars-cov2-variant</link>
	<title><![CDATA[Classification of SARS-CoV2 Variant !]]></title>
	<description><![CDATA[<p>The scientists established some guidelines for determining whether a variant is a legitimate branch of an existing lineage:</p><p>The variant should be transmitted from its original location to another "geographically distinct population"&mdash;say, another country or a province of a large and populous country.<br />It should differ from its ancestor by at least one nucleotide.<br />At least 95% of its genetic code should have been sequenced at least five times from different samples.</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</guid>
	<pubDate>Thu, 25 Oct 2018 09:05:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38004/vcfr-a-package-to-manipulate-and-visualize-vcf-data-in-r</link>
	<title><![CDATA[vcfR:  a package to manipulate and visualize VCF data in R]]></title>
	<description><![CDATA[<p><span>VcfR is an R package intended to allow easy manipulation and visualization of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices from the VCF data for use with typical R functions. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file or converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and the R environment connecting familiar software with genomic data.</span></p><p>Address of the bookmark: <a href="https://github.com/knausb/vcfR" rel="nofollow">https://github.com/knausb/vcfR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</guid>
	<pubDate>Wed, 23 Dec 2020 03:50:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/42470/the-new-corona-variant-has-23-mutations-in-all-which-is-unusually-huge</link>
	<title><![CDATA[The new corona variant has 23 mutations in all, which is unusually huge !]]></title>
	<description><![CDATA[<p>The new SARS-CoV-2 version, B.1.1.7, which was first seen in the third week of September in Kent and Greater London, has since spread to other locations in the UK. According to the COVID-19 Genomics UK Consortium (COG-UK Consortium) that analysed the genome data of the virus and identified the variant, the new variant has been spreading "rapidly" over the last four weeks and has now been detected in other locations in the UK, suggesting further spread of the variant in the region.</p><p><span>According to a<span>&nbsp;</span></span><a href="https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563"><strong><span>preliminary report</span></strong></a><span><span>&nbsp;</span>posted on December 19 by the COG-UK Consortium scientists, as of December 15, 1,623 variant genomes have been sequenced. In a<span>&nbsp;</span></span><a href="https://twitter.com/TheCGPS/status/1340749351803629569"><strong><span>December 21 tweet</span></strong></a><span>, COG-UK Consortium said that it added 2,963 more genome sequences of SARS-CoV-2, of which 942 (32%) belong to the new variant. The Consortium<span>&nbsp;</span></span><a href="https://twitter.com/CovidGenomicsUK/status/1341073233420955654"><strong><span>intends to sequence</span></strong></a><span><span>&nbsp;</span>20,000 more SARS-CoV-2 genomes in the next two weeks to further ascertain the spread of the variant.</span></p><p><span>There is no clear proof, at least not yet, that it does cause severe pandemic. But there is a justification for seriously taking the possibility. Another coronavirus lineage in South Africa has acquired one specific mutation that is also present in B.1.1.7. This variant is increasingly spreading across South Africa's coastal regions. And doctors have observed in preliminary research that individuals infected with this variant bear a higher viral load-a higher concentration of the virus in their upper respiratory tract. In many viral diseases, this is associated with more severe symptoms.</span></p><p>&nbsp;</p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36921/breakpointer-using-local-mapping-artifacts-to-support-sequence-breakpoint-discovery-from-single-end-reads</guid>
	<pubDate>Tue, 12 Jun 2018 12:41:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36921/breakpointer-using-local-mapping-artifacts-to-support-sequence-breakpoint-discovery-from-single-end-reads</link>
	<title><![CDATA[Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads]]></title>
	<description><![CDATA[Breakpointer is a fast tool for locating sequence breakpoints from the alignment of single end reads (SE) produced by next generation sequencing (NGS). It adopts a heuristic method in searching for local mapping signatures created by insertion/deletions (indels) or more complex structural variants(SVs).<p>Address of the bookmark: <a href="https://github.com/ruping/Breakpointer" rel="nofollow">https://github.com/ruping/Breakpointer</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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