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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/26424?offset=100</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30966/maftools</guid>
	<pubDate>Thu, 16 Feb 2017 11:16:01 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30966/maftools</link>
	<title><![CDATA[MafTools]]></title>
	<description><![CDATA[<p>maftools - An R package to summarize, analyze and visualize MAF files. <a href="https://github.com/PoisonAlien/maftools#introduction"></a>Introduction.</p>
<p>With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. <a href="http://cancergenome.nih.gov">The Cancer Genome Atlas</a> Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The <a href="https://wiki.nci.nih.gov/display/TCGA/TCGA+MAF+Files">resulting data</a> consisting of genetic variants is stored in the form of <a href="https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+%28MAF%29+Specification">Mutation Annotation Format</a>. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.</p>
<p>maftools is on <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f449.png" alt=":point_right:" width="20" height="20" style="border: 0px;"> <a href="http://biorxiv.org/content/early/2016/05/11/052662">bioRxiv</a> <img src="https://assets-cdn.github.com/images/icons/emoji/bowtie.png" alt=":bowtie:" title=":bowtie:" width="20" height="20" style="border: 0px; text-align: absmiddle;"></p>
<p>Please cite the below if you find this tool useful for you.</p>
<p>Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: <a href="http://dx.doi.org/10.1101/052662">http://dx.doi.org/10.1101/052662</a></p><p>Address of the bookmark: <a href="https://github.com/PoisonAlien/maftools" rel="nofollow">https://github.com/PoisonAlien/maftools</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</guid>
	<pubDate>Sat, 25 Feb 2017 17:52:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31123/biodownloader</link>
	<title><![CDATA[BioDownloader]]></title>
	<description><![CDATA[<p><strong><em>BioDownloader</em></strong> is a program for downloading and/or updating files from ftp/http servers. The program has unique features that are specifically designed to deal with bioinformatics data files and servers:</p>
<ul>
<li>optimized to work with vast amount of data and very large file sets (~ 10,000 - 100,000).</li>
<li>allows the selective retrieval of only the required files (file masks, ls-lR parsing, recursive search, updates)</li>
<li>has a built-in repository containing the settings for the most common bioinformatics download needs</li>
<li>built-in wizard for batch post-processing of downloaded files (archive extraction, file conversion, etc.)</li>
<li>capable of performing multiple download or update tasks simultaneously</li>
</ul>
<p>BioDownloader has a built-in repository containing the settings for common bioinformatics file-synchronization needs, including the Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) databases. It can post-process downloaded files, including archive extraction and file conversions.</p>
<p>http://dunbrack.fccc.edu/BioDownloader/</p><p>Address of the bookmark: <a href="http://dunbrack.fccc.edu/BioDownloader/" rel="nofollow">http://dunbrack.fccc.edu/BioDownloader/</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</guid>
	<pubDate>Fri, 17 Feb 2017 16:13:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31024/dagchainer-computing-chains-of-syntenic-genes-in-complete-genomes</link>
	<title><![CDATA[DAGchainer: Computing Chains of Syntenic Genes in Complete Genomes]]></title>
	<description><![CDATA[<p>The DAGchainer software computes chains of syntenic genes found within complete genome sequences. As input, DAGchainer accepts a list of gene pairs with sequence homology along with their genome coordinates. Using a scoring function which accounts for the distance between neighboring genes on each DNA molecule and the BLAST E-value score between homologs, maximally scoring chains of ordered gene pairs are computed and reported. This algorithm can be used to mine large evolutionary conserved regions of genomes between two organisms. Alternatively, by examining colinear sets of homologous genes found within a single genome, segmental genome duplications can be revealed.</p>
<p>This software distribution includes both the DAGchainer utility and a Java-based graphical interface that allows the inputs and outputs to be navigated and interrogated dynamically.</p><p>Address of the bookmark: <a href="http://dagchainer.sourceforge.net/" rel="nofollow">http://dagchainer.sourceforge.net/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</guid>
	<pubDate>Fri, 24 Feb 2017 04:55:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31089/conpade-genome-assembly-ploidy-estimation-from-next-generation-sequencing-data</link>
	<title><![CDATA[ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data]]></title>
	<description><![CDATA[<p><span>ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, they report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. They also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low.&nbsp;</span></p>
<p><span>https://github.com/microsoftgenomics</span></p><p>Address of the bookmark: <a href="https://github.com/microsoftgenomics" rel="nofollow">https://github.com/microsoftgenomics</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</guid>
	<pubDate>Fri, 03 Mar 2017 08:34:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31295/mycc-accurate-binning-of-metagenomic-contigs-via-automated-clustering-sequences-using-information-of-genomic-signatures-and-marker-genes</link>
	<title><![CDATA[MyCC: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes]]></title>
	<description><![CDATA[<p><span>MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments.</span></p>
<p><span>More at&nbsp;http://www.nature.com/articles/srep24175</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/sb2nhri/files/MyCC/" rel="nofollow">https://sourceforge.net/projects/sb2nhri/files/MyCC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</guid>
	<pubDate>Mon, 06 Mar 2017 03:49:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31345/prokka-tool-for-the-rapid-annotation-of-prokaryotic-genomes</link>
	<title><![CDATA[Prokka: tool for the rapid annotation of prokaryotic genomes]]></title>
	<description><![CDATA[<p>Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.prokka.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.prokka.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</guid>
	<pubDate>Tue, 07 Mar 2017 08:50:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</link>
	<title><![CDATA[COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)]]></title>
	<description><![CDATA[<p>COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.</p>
<p>News: Python version of COCACOLA is available now!</p><p>Address of the bookmark: <a href="https://github.com/younglululu/COCACOLA" rel="nofollow">https://github.com/younglululu/COCACOLA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/92/genomic-impact</guid>
	<pubDate>Wed, 10 Jul 2013 01:33:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/92/genomic-impact</link>
	<title><![CDATA[Genomic Impact]]></title>
	<description><![CDATA[<p>The ongoing genomic research in USA&nbsp;<span>contributed $31 billion to the U.S. gross national product and helped support 152,000 jobs.&nbsp;</span></p><p><span>Reference:&nbsp;<a href="http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf">http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf</a></span></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</guid>
	<pubDate>Fri, 10 Mar 2017 08:51:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</link>
	<title><![CDATA[sequenceserver]]></title>
	<description><![CDATA[<p><span>SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.</span></p>
<p><span><span>More at&nbsp;</span><a href="http://sequenceserver.com/">http://sequenceserver.com</a><span>.</span></span></p><p>Address of the bookmark: <a href="https://github.com/wurmlab/sequenceserver" rel="nofollow">https://github.com/wurmlab/sequenceserver</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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