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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29382?offset=1020</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</guid>
	<pubDate>Mon, 27 Nov 2017 16:24:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34463/single-cell-rnaseq-data-analysis-tutorial</link>
	<title><![CDATA[Single Cell RNAseq data analysis tutorial !!]]></title>
	<description><![CDATA[<ul>
<li>A major breakthrough (replaced microarrays) in the late 00&rsquo;s and has been widely used since</li>
<li>Measures the&nbsp;average expression level&nbsp;for each gene across a large population of input cells</li>
<li>Useful for comparative transcriptomics, e.g.&nbsp;samples of the same tissue from different species</li>
<li>Useful for quantifying expression signatures from ensembles, e.g.&nbsp;in disease studies</li>
<li>Insufficient&nbsp;for studying heterogeneous systems, e.g.&nbsp;early development studies, complex tissues (brain)</li>
<li>Does&nbsp;not&nbsp;provide insights into the stochastic nature of gene expression</li>
</ul><p>Following are the useful links:</p><p><a href="http://hemberg-lab.github.io/scRNA.seq.course/scRNA-seq-course.pdf" target="_blank">Single Cell RNAseq data analysis Tutorial</a></p><p><a href="https://f1000research.com/articles/5-2122/v2" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data</a></p><p><a href="https://www.bioconductor.org/help/workflows/simpleSingleCell/" target="_blank">A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor</a></p><p>SCell: single-cell RNA-seq analysis software</p><p><a href="https://github.com/diazlab/SCell">https://github.com/diazlab/SCell</a></p><p>Beta-Poisson model for single-cell RNA-seq data analyses</p><p><a href="https://github.com/nghiavtr/BPSC">https://github.com/nghiavtr/BPSC</a></p><p>Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis</p><p><a href="https://research.cchmc.org/pbge/sincera.html">https://research.cchmc.org/pbge/sincera.html</a></p><p>SC3 &ndash; consensus clustering of single-cell RNA-Seq data</p><p><a href="http://biorxiv.org/content/early/2016/09/02/036558">http://biorxiv.org/content/early/2016/09/02/036558</a></p><p>Citrus: A toolkit for single cell sequencing analysis</p><p><a href="http://biorxiv.org/content/early/2016/09/14/045070">http://biorxiv.org/content/early/2016/09/14/045070</a></p><p>Single-Cell Resolution of Temporal Gene Expression during Heart Development</p><p><a href="http://www.cell.com/developmental-cell/fulltext/S1534-5807%2816%2930682-7">http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7</a></p><p>Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects</p><p><a href="http://biorxiv.org/content/early/2016/11/15/087775">http://biorxiv.org/content/early/2016/11/15/087775</a></p><p>Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes</p><p><a href="http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract">http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract</a></p><p>SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation</p><p><a href="http://biorxiv.org/content/early/2016/11/21/088856">http://biorxiv.org/content/early/2016/11/21/088856</a></p><p>SCOUP is a probabilistic model to analyze single-cell expression data during differentiation</p><p><a href="https://github.com/hmatsu1226/SCOUP">https://github.com/hmatsu1226/SCOUP</a></p><p>scLVM is a modelling framework for single-cell RNA-seq data</p><p><a href="https://github.com/PMBio/scLVM">https://github.com/PMBio/scLVM</a></p><p>Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories</p><p><a href="https://github.com/jw156605/SLICER">https://github.com/jw156605/SLICER</a></p><p>SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality</p><p><a href="http://www.morgridge.net/SinQC.html">http://www.morgridge.net/SinQC.html</a></p><p>TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis</p><p><a href="https://github.com/zji90/TSCAN">https://github.com/zji90/TSCAN</a></p><p>Visualization and cellular hierarchy inference of single-cell data using SPADE</p><p><a href="http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html">http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html</a></p><p>OEFinder: Identify ordering effect genes in single cell RNA-seq data</p><p><a href="https://github.com/lengning/OEFinder">https://github.com/lengning/OEFinder</a></p>]]></description>
	<dc:creator>Robert M Willioms</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/41924/senior-scientist-bioinformatics-it-at-regional-centre-for-biotechnology</guid>
  <pubDate>Tue, 30 Jun 2020 22:04:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[Senior Scientist (Bioinformatics/ IT) at Regional Centre for Biotechnology]]></title>
  <description><![CDATA[
<p>Regional Centre for Biotechnology</p>

<p>An Institution of National Importance established by Dept. of<br />Biotechnology, Govt. of India Under the auspices of UNESCO</p>

<p>Advertisement No. RCB/IBDC/01/2020/Recruitment/HR</p>

<p>Recruitment For Contractual Positions Under The Project<br />Indian Biological Data Centre (IBDC) Phase-1</p>

<p>Regional Centre for Biotechnology (RCB) invites online applications from suitably qualified, dynamic, result-oriented and dedicated candidates for the following positions under the project Indian Biological Data Centre (BIDC) Phase-1 on contract basis:</p>

<p>Industry: Biotechnology</p>

<p>Location: Faridabad (Haryana, India)</p>

<p>Project Head - 1</p>

<p>Senior Scientist (Bioinformatics/ IT) - 1</p>

<p>For other details, visit: www.rcb.res.in. Last date for receipt of online application is 18th July 2020.</p>

<p>Registrar</p>

<p>Regional Centre for Biotechnology<br />Faridabad-Gurgaon Expressway,<br />Faridabad - 121001</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42172/sr-scientist-bioinformatics-vacancies-at-indian-institute-of-toxicology-research-india</guid>
  <pubDate>Tue, 01 Sep 2020 07:21:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[Sr. Scientist Bioinformatics Vacancies at Indian Institute of Toxicology Research, India]]></title>
  <description><![CDATA[
<p>Start date of online Registration: Wednesday August 19, 2020 11:00 Hrs IST<br />Last date for Registration: Monday September 21, 2020 17:30 Hrs IST<br />Last date for submission of online application: Monday September 21, 2020 17:30 Hrs IST<br />Last date of Receipt of physical copy of application at CSIR-IITR: Tuesday October 05, 2020 17:30 Hrs IST</p>

<p>Pay Matrix Level-12<br />No. of Post-01<br />(UR)<br />Post – Sr. Scientist<br />Area Bioinformatics<br />Age limit : 37 years<br />PhD in Computational Biology/Bioinformatics with 2 years experience in desired area<br />Or<br />ME/M.Tech in Bioinformatics or Genome Informatics or Genetic Engineering with 3 years experience in desired area<br />Experience of understanding fundamental science behind Artificial Intelligence, machine learning, novel Artificial Intelligence algorithms and architectures, software engineering principles for Artificial Intelligence, natural language processing with proficiency in programming as evident by publications in SCI journals with high impact factor. To be part a group of scientists working in the area of genomics, running the central<br />bioinformatics facility, developing independent projects and providing bioinformatics support to the user scientists of the Institute.</p>

<p>More at </p>

<p>http://14.139.62.50/CSIR-IITR%20Scientist%20Recruitment%20Adv%202020.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</guid>
	<pubDate>Sat, 25 Jan 2020 13:28:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40611/deepvariant-an-analysis-pipeline-that-uses-a-deep-neural-network-to-call-genetic-variants-from-next-generation-dna-sequencing-data</link>
	<title><![CDATA[DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.]]></title>
	<description><![CDATA[<p><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.</span></p>
<p><span><span>DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on&nbsp;</span><a href="https://github.com/google/nucleus">Nucleus</a><span>, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the&nbsp;</span><a href="https://www.tensorflow.org/">TensorFlow</a><span>&nbsp;machine learning framework.</span></span></p>
<p><span><a href="https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html">https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html</a></span></p>
<p><span><a href="https://www.biorxiv.org/content/10.1101/092890v6">https://www.biorxiv.org/content/10.1101/092890v6</a></span></p>
<p><span><img src="https://4.bp.blogspot.com/-2KlXZO60sWE/WiGc8qlZfxI/AAAAAAAACOs/s1pNiKI8jsAvJLr1E_po5udDO8eObm_awCLcBGAs/s640/image3.png" width="640" height="427" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/google/deepvariant" rel="nofollow">https://github.com/google/deepvariant</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42264/bioinformatics-jobs-at-acrannolife</guid>
  <pubDate>Sun, 25 Oct 2020 22:51:35 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics jobs at Acrannolife]]></title>
  <description><![CDATA[
<p>Acrannolife are looking for skilled Bioinformatics Scientists with a minimum of 2yrs Experience in NGS data analysis including Nanopore Sequencing.</p>

<p>This is an opportunity to work on projects that would fundamentally alter the way certain chronic conditions are treated and monitored.</p>

<p>About acrannolife:</p>

<p>We are a team of Post Docs, PhDs, Engineers, Clinicians, and MBAs working towards a future where biology intersects with software(Computational Biology).</p>

<p>We are incubated in Atal Incubation Centre - CCMB and have been backed by some of the leading thought leaders ranging from business to clinical practices.</p>

<p>Interested candidates can fill this form. https://lnkd.in/gtq47hy</p>

<p>and send their CV to hr@acrannolife.com</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</guid>
	<pubDate>Fri, 21 Feb 2020 00:33:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41209/juicebox-visualization-and-analysis-software-for-hi-c-data</link>
	<title><![CDATA[Juicebox: Visualization and analysis software for Hi-C data]]></title>
	<description><![CDATA[<p>Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox,&nbsp;<a href="https://github.com/theaidenlab/juicer/wiki/Download">Juicer Tools</a>, and&nbsp;<a href="https://aidenlab.org/assembly/">Assembly Tools</a>.&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki/Download">Download Juicebox here</a>, or use&nbsp;<a href="https://aidenlab.org/juicebox">Juicebox on the web</a>. Detailed documentation is available&nbsp;<a href="https://github.com/theaidenlab/juicebox/wiki">on the wiki</a>. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.</p>
<p>Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website&nbsp;<a href="https://aidenlab.org/assembly">https://aidenlab.org/assembly</a>&nbsp;for more details on how to use Juicebox for assembly.</p>
<p>GUI at&nbsp;<a href="https://aidenlab.org/juicebox/">https://aidenlab.org/juicebox/</a></p><p>Address of the bookmark: <a href="https://github.com/aidenlab/Juicebox" rel="nofollow">https://github.com/aidenlab/Juicebox</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42374/postdoc-in-comparative-genomics</guid>
  <pubDate>Tue, 08 Dec 2020 09:26:40 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoc in comparative genomics]]></title>
  <description><![CDATA[
<p>We are looking for a highly motivated researcher for an 18 month postdoctoral position collaborating in an exciting project on comparative genomics of marine fish and shellfish species. In the project, we use genome resequencing data from a range of species to reconstruct the demographic history and characterize genomic signals associated with population divergence and local adaptation in high gene flow scenarios. The work will improve our understanding of interacting evolutionary processes and provide valuable data for securing sustainable management and conservation of exploited resources. Applicants are encouraged to develop their own research ideas within this framework.</p>

<p>The fellowship is part of a larger Nordic collaborative project, MarGen_II, financed by the EU Interreg Öresund-Kattegat-Skagerrak Programme, the Danish Rod and Net License Funds and the National Institute of Aquatic Resources (DTU Aqua). The project will primarily be carried out in the population genetics group, Section for Marine Living Resources, situated in Silkeborg, Denmark. DTU Aqua is an institute at the Technical University of Denmark. In addition, the position offers many opportunities for collaborating with Nordic and other European colleagues in the field.</p>

<p>Application:<br />Apply online at<br />https://www.dtu.dk/english/About/JOB-and-CAREER/vacant-positions/job?id=d198fd80-4856-4a56-943d-485106026504.<br />The deadline is 4 January 2021. For further information, please contact<br />Senior Researcher Jakob Hemmer-Hansen, jhh@aqua.dtu.dk.</p>

<p>You can read more about DTU Aqua at www.aqua.dtu.dk<br />and the population genetics group at<br />https://www.aqua.dtu.dk/english/research/population_genetics.</p>

<p>All interested candidates irrespective of age, gender, race, disability,<br />religion or ethnic background are encouraged to apply.</p>

<p>Jakob Hemmer Hansen</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/42670/icgeb-bioinformatics-job</guid>
  <pubDate>Sat, 23 Jan 2021 21:01:55 -0600</pubDate>
  <link></link>
  <title><![CDATA[ICGEB Bioinformatics Job]]></title>
  <description><![CDATA[
<p>The following vacancies are available in the various ongoing bioinformatics projects at.<br />Translational Bioinformatics Group (https://www.icgeb.org/dinesh-gupta/), ICGEB, New Delhi, India. Shortlisted candidates will be welcomed for an on-line interview at ICGEB. Only the chosen applicants will be informed individually. Preference will be given to the applicants with experience related to Bioinformatics as well as Computational area.</p>

<p>Interested applicants must submit their complete, updated Curriculum Vitae, mentioning details of two references as well as various other details at – http://14.139.62.220/survey/index.php/2021/01/21/icgeb-dbt-project-vacancy/</p>

<p>The last date of submission of applications is January 31st, 2021.</p>

<p>Research Associate : PhD. Degree in Computational Biology/Bioinformatics.</p>

<p>Consolidated Salary: 58280/- pm (including HRA).</p>

<p>More at https://www.icgeb.org/project-positions-translational-bioinformatics-group/ and https://www.icgeb.org/category/vacancies/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</guid>
	<pubDate>Wed, 18 Aug 2021 00:02:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</link>
	<title><![CDATA[Kmer: a suite of tools for DNA sequence analysis]]></title>
	<description><![CDATA[<p>More at&nbsp;https://help.rc.ufl.edu/doc/Kmer</p>
<p>This also includes:</p>
<ul>
<li>A2Amapper: ATAC, Assembly to Assembly Comparision tool:
<ul>
<li>Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).</li>
</ul>
</li>
</ul>
<ul>
<li>Sim4db:
<ul>
<li>Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.</li>
</ul>
</li>
</ul>
<ul>
<li>LEAFF:
<ul>
<li>LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.</li>
</ul>
</li>
</ul>
<ul>
<li>Meryl:
<ul>
<li>An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://help.rc.ufl.edu/doc/Kmer" rel="nofollow">https://help.rc.ufl.edu/doc/Kmer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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