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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40204?offset=380</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</guid>
	<pubDate>Fri, 21 Oct 2016 04:54:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29485/ribbon</link>
	<title><![CDATA[Ribbon !!]]></title>
	<description><![CDATA[<p><span>Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.</span></p>
<p>Script at&nbsp;https://github.com/MariaNattestad/ribbon</p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29574/beagle</guid>
	<pubDate>Thu, 27 Oct 2016 11:19:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29574/beagle</link>
	<title><![CDATA[Beagle]]></title>
	<description><![CDATA[<p>Beagle is a software package that performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection.</p>
<p>Beagle version 4.1 has a more accurate genotype phasing algorithm and a very fast and accurate genotype imputation algorithm. Version 4.1 also has several changes to the command line arguments which are described in the&nbsp;<a href="http://faculty.washington.edu/browning/beagle/release_notes" target="_blank">release notes</a>. The "ped" argument has no effect in version 4.1. If your data contains nuclear families and you want to model the parent-offspring relationships when phasing genotypes, please use&nbsp;<a href="https://faculty.washington.edu/browning/beagle/b4_0.html">version 4.0</a>.</p>
<p>If you use Beagle 4.1 in a published analysis, please report the program version and cite the appropriate article.</p>
<p>The citation for Beagle's phasing algorithm is:</p>
<p>S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097.<a href="http://dx.doi.org/doi:10.1086/521987" target="_blank">doi:10.1086/521987</a></p>
<p>The citation for Beagle's genotype imputation algorithm is:</p>
<p>B L Browning and S R Browning (2016). Genotype imputation with millions of reference samples. Am J Hum Genet 98:116-126.<a href="http://dx.doi.org/doi:10.1016/j.ajhg.2015.11.020" target="_blank">doi:10.1016/j.ajhg.2015.11.020</a></p>
<p>The citation for Beagle's IBD detection algorithm is:</p>
<p>B L Browning and S R Browning (2013). Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194(2):459-71.<a href="http://dx.doi.org/doi:10.1534/genetics.113.150029" target="_blank">doi:10.1534/genetics.113.150029</a></p><p>Address of the bookmark: <a href="http://faculty.washington.edu/browning/beagle/beagle.html" rel="nofollow">http://faculty.washington.edu/browning/beagle/beagle.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29588/research-associate-and-junior-research-fellow-at-north-eastern-hill-university-tura-meghalaya</guid>
  <pubDate>Fri, 28 Oct 2016 09:54:43 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Associate and Junior Research Fellow at North-Eastern Hill University - Tura, Meghalaya]]></title>
  <description><![CDATA[
<p>Research Associate and Junior Research Fellow <br />North-Eastern Hill University - Tura, Meghalaya <br />₹18,000 a month<br />Applications are invited for the post of Research Associate and JRF in the DBT sponsored Bioinformatics Infrastructure Facility (BIF), posts are purely temporary and terminable at anytime without prior notice or assigning any reason thereof. </p>

<p>Research Associate : <br />Essential Qualification: Ph.D in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.36000-/- + Admissible 10% HRA per month <br />Age: Below 35 years </p>

<p>Junior Research Fellow <br />Essential Qualification: M.Sc in Bioinformatics/Biotechnology/Life Science from a reocngised univeristy/institute <br />Pay: Rs.18000-/- + per month <br />Age: Below 35 years </p>

<p>Last date for receving application by mail or post is 08.11.2016 </p>

<p>Company Info. <br />North-Eastern Hill University </p>

<p>Bioinformatics Infrastructure Facility (BIF) Department of RDAP North-Eastern Hill University, Tura Campus Tura-794002, Meghalaya</p>

<p>More at http://www.nehu.ac.in/Advertisements/BIFTuraManpowerAdvt_25102016.pdf</p>
]]></description>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</guid>
	<pubDate>Fri, 04 Nov 2016 05:02:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29620/hybpiper</link>
	<title><![CDATA[HybPiper]]></title>
	<description><![CDATA[<p>HybPiper was designed for targeted sequence capture, in which DNA sequencing libraries are enriched for gene regions of interest, especially for phylogenetics. HybPiper is a suite of Python scripts that wrap and connect bioinformatics tools in order to extract target sequences from high-throughput DNA sequencing reads.</p>
<p>Targeted bait capture is a technique for sequencing many loci simultaneously based on bait sequences. HybPiper pipeline starts with high-throughput sequencing reads (for example from Illumina MiSeq), and assigns them to target genes using BLASTx or BWA. The reads are distributed to separate directories, where they are assembled separately using SPAdes. The main output is a FASTA file of the (in frame) CDS portion of the sample for each target region, and a separate file with the translated protein sequence.</p>
<p>HybPiper also includes post-processing scripts, run after the main pipeline, to also extract the intronic regions flanking each exon, investigate putative paralogs, and calculate sequencing depth. For more information,&nbsp;<a href="https://github.com/mossmatters/HybPiper/wiki/">please see our wiki</a>.</p>
<p>HybPiper is run separately for each sample (single or paired-end sequence reads). When HybPiper generates sequence files from the reads, it does so in a standardized directory hierarchy. Many of the post-processing scripts rely on this directory hierarchy, so do not modify it after running the initial pipeline. It is a good idea to run the pipeline for each sample from the same directory. You will end up with one directory per run of HybPiper, and some of the later scripts take advantage of this predictable directory structure.</p><p>Address of the bookmark: <a href="https://github.com/mossmatters/HybPiper" rel="nofollow">https://github.com/mossmatters/HybPiper</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</guid>
	<pubDate>Fri, 04 Nov 2016 12:50:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/29638/r-graphical-cookbook-by-winston-chang</link>
	<title><![CDATA[R Graphical Cookbook by Winston Chang]]></title>
	<description><![CDATA[<p>R Graphical Cookbook by Winston Chang</p><p>A very nice book by Winston Chang for R ethusiast. The R code presented in these pages is the R code actually used to produce the Figures in the book. There will be differences compared to the code chunks shown in the text of the book, but in most cases the differences will be that these pages contain additional code to lay out multiple plots on a single "page".</p><p>The code presented for each figure is self-contained, i.e., all code required to produce the figure is included. This means that there is sometimes considerable overlap of code between several figures  In some cases, it may be necessary to install an add-on package from CRAN to get the code to run.</p><p>More books at http://www.e-reading.club/bookreader.php/137370/C486x_APPb.pdf</p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/29638" length="37521" type="image/png" />
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29883/ra-bioinformatics-at-school-of-computational-integrative-sciences-jnu-india</guid>
  <pubDate>Fri, 18 Nov 2016 03:57:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at School of Computational &amp; Integrative Sciences, JNU, India]]></title>
  <description><![CDATA[
<p>School of Computational &amp; Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi – 110067</p>

<p>Date: Nov 11th. 2016                                                            Last Date:  Nov 25th. 2016</p>

<p>PROJECT ID: 632</p>

<p>The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh,  School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067</p>

<p>NB:For all Bioinformatics posts, preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.</p>

<p>RA / Research Associate (Metabolic engineering/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in  Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/ system Biology/ Analysis of Network Biology. Published paper in the field is a must to prove the experience.<br />Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , managing the project portal, preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.</p>

<p>RA / Research Associate (Chemo-informatics/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in Bioinformatics/ computational biology/ Biophysics/Computer Science. Computational and Chemical structure related experience is a necessary qualification proven by paper published and program developed. <br />Desired Skills:  Research experience in Chemical scaffold mapping, in silico Spectral analysis, Biological Database Designing &amp; Integration is required. Individual is responsible to develop methods related to metabolite identification, Testing and refining and integrate LIMS with IIIT Hyderabad and will be expected to communicate with user groups.</p>

<p>Project SRF (Bioinformatics/Programming)</p>

<p>Salary: As per DBT rules<br />Vacancy: 1<br />Essential Qualifications: Masters/B Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building &amp; maintenance ,high throughput data handling and analysis etc. For M.Sc/B.Tec, Published paper  in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</guid>
	<pubDate>Wed, 30 Nov 2016 04:09:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30002/excavator2tool</link>
	<title><![CDATA[EXCAVATOR2tool]]></title>
	<description><![CDATA[<p><span>EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.</span><br><span>EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it&rsquo;s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/excavator2tool/" rel="nofollow">https://sourceforge.net/projects/excavator2tool/</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30198/faculty-at-indian-institute-of-science-education-and-research-berhampur</guid>
  <pubDate>Mon, 19 Dec 2016 03:34:26 -0600</pubDate>
  <link></link>
  <title><![CDATA[Faculty at Indian Institute of Science Education and Research Berhampur]]></title>
  <description><![CDATA[
<p>Advt. No: IISERBPR/DoFA/2016/2</p>

<p>Advertisement for Faculty Positions</p>

<p>The IISER Berhampur, an Institute of national importance, established through an act of Parliament is an autonomous organization under the Ministry of HRD, Govt. of India, to promote quality education and cutting edge research in basic sciences and to provide a platform for the faculty to engage in high quality education, at undergraduate and postgraduate levels. The Institute invites applications for faculty positions at the level of Assistant Professor (C) /Assistant Professor in the following disciplines:</p>

<p>1. Biological Sciences</p>

<p>2. Chemistry</p>

<p>3. Computer Sciences</p>

<p>4. Mathematics</p>

<p>5. Physics</p>

<p>Only hard copy of application in the prescribed format, via Speed Post should be sent to the Dean, Faculty Affairs, IISER Berhampur, Industrial Training Institute (ITI) Berhampur, Engineering School Road, Berhampur - 760 010, Ganjam District, Odisha, before 1700 hrs., December 30, 2016.</p>

<p>http://www.iiserbpr.ac.in</p>

<p>More Info : http://www.iiserbpr.ac.in/vacancies/Advertisement%20for%20Faculty%20Positions%20at%20IISER%20Berhampur.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</guid>
	<pubDate>Thu, 08 Dec 2016 05:08:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30076/sga-string-graph-assembler</link>
	<title><![CDATA[SGA: String Graph Assembler]]></title>
	<description><![CDATA[<p><span>SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.</span></p>
<p><span>More at</span></p>
<p><span>https://github.com/jts/sga</span></p>
<p>SGA dependencies:<br> -google sparse hash library (http://code.google.com/p/google-sparsehash/)<br> -the bamtools library (https://github.com/pezmaster31/bamtools)<br> -zlib (http://www.zlib.net/)<br> -(optional but suggested) the jemalloc memory allocator (http://www.canonware.com/jemalloc/download.html)</p><p>Address of the bookmark: <a href="https://github.com/jts/sga" rel="nofollow">https://github.com/jts/sga</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</guid>
	<pubDate>Fri, 09 Dec 2016 04:19:07 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial</link>
	<title><![CDATA[Velvet tutorial]]></title>
	<description><![CDATA[<p><span>The objective of this activity is to help you understand how to run&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/velvet/" title="Velvet">Velvet</a><span>&nbsp;in general, how to accurately estimate the insert size of a paired-end library through the use of&nbsp;</span><a href="http://evomics.org/resources/software/genomics-software/assembly/bowtie/" title="Bowtie">Bowtie</a><span>, the primary parameters of velvet, and the process involved in producing a&nbsp;</span><em>de novo</em><span>&nbsp;assembly from Illumina reads.</span></p>
<p>http://evomics.org/learning/assembly-and-alignment/velvet/</p><p>Address of the bookmark: <a href="http://evomics.org/learning/assembly-and-alignment/velvet/" rel="nofollow">http://evomics.org/learning/assembly-and-alignment/velvet/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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