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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/34569?offset=100</link>
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	<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/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/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</guid>
	<pubDate>Mon, 06 Mar 2017 04:03:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31351/maxbin-software-for-binning-assembled-metagenomic-sequences-based-on-an-expectation-maximization-algorithm</link>
	<title><![CDATA[MaxBin: software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm.]]></title>
	<description><![CDATA[<p><span>MaxBin is software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users can understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page.</span><br><br><span>Users can use MEGAN or similar software on MaxBin bins to find the taxonomy of each bin after the binning process is finished.</span></p>
<p>https://academic.oup.com/bioinformatics/article/32/4/605/1744462/MaxBin-2-0-an-automated-binning-algorithm-to<br><br><span>The most recent version of MaxBin is 2.2, which supports the analysis of coassemblies of multiple samples. It is available at this JBEI downloads sites as well as&nbsp;</span><a href="https://sourceforge.net/projects/maxbin/" target="_blank">MaxBin</a><span>&nbsp;and&nbsp;</span><a href="https://sourceforge.net/projects/maxbin2/" target="_blank">MaxBin 2.0</a><span>&nbsp;sourceforge sites.</span></p><p>Address of the bookmark: <a href="http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html" rel="nofollow">http://downloads.jbei.org/data/microbial_communities/MaxBin/MaxBin.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</guid>
	<pubDate>Tue, 07 Mar 2017 08:59:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31377/groopm-metagenomic-binning-toolset</link>
	<title><![CDATA[GroopM: Metagenomic binning toolset]]></title>
	<description><![CDATA[<p>GroopM is a metagenomic binning toolset. It leverages spatio-temoral<br>dynamics (differential coverage) to accurately (and almost automatically)<br>extract population genomes from multi-sample metagenomic datasets.</p>
<p>GroopM is largely parameter-free. Use: groopm -h for more info.</p>
<p>For installation and usage instructions see : http://ecogenomics.github.io/GroopM/</p><p>Address of the bookmark: <a href="https://github.com/ecogenomics/GroopM" rel="nofollow">https://github.com/ecogenomics/GroopM</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</guid>
	<pubDate>Tue, 16 May 2017 08:56:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[NCBI Prokaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p>
<p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p>
<p>NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of&nbsp;the pipeline in&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK174280/">NCBI Handbook chapter</a>. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p>
<p>https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</guid>
	<pubDate>Mon, 09 Jul 2018 05:20:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37257/asar-advanced-metagenomic-sequence-analysis-in-r</link>
	<title><![CDATA[ASAR: Advanced metagenomic Sequence Analysis in R]]></title>
	<description><![CDATA[<p><span>An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.</span></p>
<p><span><span>To read the manual, please click the link&nbsp;</span><a href="https://askarbek-orakov.github.io/ASAR/">https://askarbek-orakov.github.io/ASAR/</a></span></p><p>Address of the bookmark: <a href="https://github.com/Askarbek-orakov/ASAR" rel="nofollow">https://github.com/Askarbek-orakov/ASAR</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</guid>
	<pubDate>Wed, 29 Nov 2017 16:44:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34488/scripts-for-the-analysis-of-hgt-in-genome-sequence-data</link>
	<title><![CDATA[Scripts for the analysis of HGT in genome sequence data.]]></title>
	<description><![CDATA[<p><span>Scripts for the analysis of HGT in genome sequence data</span></p><p>Address of the bookmark: <a href="https://github.com/reubwn/hgt" rel="nofollow">https://github.com/reubwn/hgt</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</guid>
	<pubDate>Wed, 27 Nov 2019 05:32:33 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40298/environment-for-tree-exploration-ete-is-a-python-programming-toolkit-that-assists-in-the-recontruction-manipulation-analysis-and-visualization-of-phylogenetic-trees</link>
	<title><![CDATA[Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees]]></title>
	<description><![CDATA[<p><span>The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).</span></p>
<p><span>Other tools</span></p>
<p><span><a href="https://github.com/shenwei356/taxonkit">https://github.com/shenwei356/taxonkit</a></span></p>
<p>&nbsp;</p>
<ul>
<li>ETE, version:&nbsp;<a href="https://pypi.org/project/ete3/3.1.1/">3.1.1</a></li>
<li>BioPython, version:&nbsp;<a href="https://pypi.org/project/biopython/1.73/">1.73</a></li>
<li>taxadb, version:&nbsp;<a href="https://pypi.org/project/taxadb/0.9.0">0.10.1</a></li>
<li>TaxonKit, version:&nbsp;<a href="https://github.com/shenwei356/taxonkit/releases/tag/0.10.1">0.5.0</a></li>
</ul><p>Address of the bookmark: <a href="https://pypi.org/project/ete3/3.1.1/" rel="nofollow">https://pypi.org/project/ete3/3.1.1/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/42559/sample-bandage-input-file-for-visual-analysis</guid>
	<pubDate>Wed, 06 Jan 2021 03:51:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/42559/sample-bandage-input-file-for-visual-analysis</link>
	<title><![CDATA[Sample bandage input file for visual analysis]]></title>
	<description><![CDATA[<p>Sample bandage input file for visual analysis ...</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/42559" length="112199" type="text/plain" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</guid>
	<pubDate>Fri, 14 Apr 2017 06:27:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32154/decostar-detection-of-co-evolution</link>
	<title><![CDATA[DeCoSTAR - Detection of Co-evolution]]></title>
	<description><![CDATA[<p><span>DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.</span><br><span>Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the&nbsp;</span><a href="http://mbb.univ-montp2.fr/MBB/download_sources/16__TERA">ecceTERA package</a><span>, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.&nbsp;</span><br><span>DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.</span></p><p>Address of the bookmark: <a href="http://pbil.univ-lyon1.fr/software/DeCoSTAR/" rel="nofollow">http://pbil.univ-lyon1.fr/software/DeCoSTAR/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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