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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41030?</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</guid>
	<pubDate>Sat, 02 Jan 2021 07:05:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads</link>
	<title><![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]></title>
	<description><![CDATA[<p><span>Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.</span></p><p>Address of the bookmark: <a href="https://github.com/tseemann/shovill" rel="nofollow">https://github.com/tseemann/shovill</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</guid>
	<pubDate>Fri, 13 Aug 2021 07:44:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43254/quasr-quantification-and-annotation-of-short-reads-in-r</link>
	<title><![CDATA[QuasR: Quantification and annotation of short reads in R]]></title>
	<description><![CDATA[<p>The <em><a href="https://bioconductor.org/packages/3.14/QuasR">QuasR</a></em> package (short for <em>Qu</em>antify and <em>a</em>nnotate <em>s</em>hort reads in <em>R</em>) integrates the functionality of several <strong>R</strong> packages (such as <em><a href="https://bioconductor.org/packages/3.14/IRanges">IRanges</a></em> <span>(Lawrence et al. 2013)</span> and <em><a href="https://bioconductor.org/packages/3.14/Rsamtools">Rsamtools</a></em>) and external software (e.g.&nbsp;<code>bowtie</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rbowtie">Rbowtie</a></em> package, and <code>HISAT2</code>, through the <em><a href="https://bioconductor.org/packages/3.14/Rhisat2">Rhisat2</a></em> package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single <strong>R</strong> script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.</p><p>Address of the bookmark: <a href="https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html" rel="nofollow">https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</guid>
	<pubDate>Sun, 14 Mar 2021 09:42:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</link>
	<title><![CDATA[AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads]]></title>
	<description><![CDATA[<p><span>AlignGraph2 is the second version of&nbsp;</span><a href="https://github.com/baoe/AlignGraph">AlignGraph</a><span>&nbsp;for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.</span></p>
<p><span>More at&nbsp;https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772</span></p><p>Address of the bookmark: <a href="https://github.com/huangs001/AlignGraph2" rel="nofollow">https://github.com/huangs001/AlignGraph2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37563/colormap-correcting-long-reads-by-mapping-short-reads</guid>
	<pubDate>Mon, 20 Aug 2018 14:17:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37563/colormap-correcting-long-reads-by-mapping-short-reads</link>
	<title><![CDATA[CoLoRMap: Correcting Long Reads by Mapping short reads]]></title>
	<description><![CDATA[<p><span>Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characterized by a high error rate, and assembling from long reads require a high depth of coverage. This motivates the development of hybrid approaches that leverage the high quality of short reads to correct errors in long reads.We introduce CoLoRMap, a hybrid method for correcting noisy long reads, such as the ones produced by PacBio sequencing technology, using high-quality Illumina paired-end reads mapped onto the long reads. Our algorithm is based on two novel ideas: using a classical shortest path algorithm to find a sequence of overlapping short reads that minimizes the edit score to a long read and extending corrected regions by local assembly of unmapped mates of mapped short reads. Our results on bacterial, fungal and insect data sets show that CoLoRMap compares well with existing hybrid correction methods.The source code of CoLoRMap is freely available for non-commercial use at https://github.com/sfu-compbio/colormap</span></p>
<p><span>ehaghshe@sfu.ca or cedric.chauve@sfu.ca</span></p><p>Address of the bookmark: <a href="https://github.com/sfu-compbio/colormap" rel="nofollow">https://github.com/sfu-compbio/colormap</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Mon, 17 Aug 2020 05:25:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p>SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol>
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</guid>
	<pubDate>Tue, 05 Sep 2023 07:31:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44373/mitohifi-a-python-pipeline-for-mitochondrial-genome-assembly-from-pacbio-high-fidelity-reads</link>
	<title><![CDATA[MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads]]></title>
	<description><![CDATA[<p dir="auto">MitoHiFi v3.2 is a python pipeline distributed under&nbsp;<a href="https://github.com/marcelauliano/MitoHiFi/blob/master/LICENSE">MIT License</a>&nbsp;!</p>
<p dir="auto">MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project (DToL)</p>
<p dir="auto">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05385-y&nbsp;</p>
<p dir="auto"><a href="https://github.com/marcelauliano/MitoHiFi/blob/master/docs/dtol-logo-round-300x132.png" target="_blank"><img src="https://github.com/marcelauliano/MitoHiFi/raw/master/docs/dtol-logo-round-300x132.png" alt="" style="border: 0px; border: 0px;"></a></p><p>Address of the bookmark: <a href="https://github.com/marcelauliano/MitoHiFi" rel="nofollow">https://github.com/marcelauliano/MitoHiFi</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44595/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Sat, 06 Jul 2024 04:29:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44595/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p dir="auto">SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol dir="auto">
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</guid>
	<pubDate>Tue, 22 Jan 2019 06:26:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38762/katuali-is-a-flexible-consensus-pipeline-implemented-in-snakemake-to-basecall-assemble-and-polish-oxford-nanopore-technologies-sequencing-data</link>
	<title><![CDATA[Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies&#039; sequencing data]]></title>
	<description><![CDATA[<ul>
<li>Run a pipeline processing fast5s to a consensus in a single command.</li>
<li>Recommended fixed "standard" and "fast" pipelines.</li>
<li>Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.</li>
<li>Seemless distribution of tasks over local or distributed compute.</li>
<li>Highly configurable.</li>
<li>Open source (Mozilla Public License 2.0).</li>
</ul>
<p>Documentation can be found at&nbsp;<a href="https://nanoporetech.github.io/katuali/">https://nanoporetech.github.io/katuali/</a>.</p><p>Address of the bookmark: <a href="https://github.com/nanoporetech/katuali" rel="nofollow">https://github.com/nanoporetech/katuali</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</guid>
	<pubDate>Sat, 24 Aug 2013 06:01:37 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3868/next-generation-sequencing-ngs-tutorials</link>
	<title><![CDATA[Next Generation Sequencing (NGS) Tutorials]]></title>
	<description><![CDATA[<p>Institute of computational biomedicine, Cornell University provide an NGS workshop tutorial at&nbsp;<a href="http://chagall.med.cornell.edu/NGScourse/">http://chagall.med.cornell.edu/NGScourse/</a>&nbsp;</p>
<p>You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit.&nbsp;</p>
<p>Understanding the basics of genome sequencing:</p>
<p>Tutorial by Luke Jostins.</p>
<p>http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/</p>
<p>http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/</p>
<p>A window into third-generation sequencing</p>
<p>http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf</p>
<p>==============================================</p>
<p>NGS data analysis pipelines</p>
<ul>
<li><strong>Detecting and annotating genetic variations using the HugeSeq pipeline</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1038/nbt.2134">10.1038/nbt.2134</a></li>
<li><strong> NARWHAL, a primary analysis pipeline for NGS data</strong> <a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc">http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc</a></li>
<li><strong>RseqFlow: Workflows for RNA-Seq data analysis</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1093/bioinformatics/btr441">10.1093/bioinformatics/btr441</a></li>
<li><strong>ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence</strong>&nbsp;&nbsp;<a href="http://dx.doi.org/10.1186/1471-2164-12-285">10.1186/1471-2164-12-285</a></li>
<li><strong>A framework for variation discovery and genotyping using next-generation DNA sequencing data</strong>&nbsp; PubMed: <a href="http://www.ncbi.nlm.nih.gov/pubmed/21478889">21478889</a></li>
<li><strong>SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects</strong>&nbsp; DOI: <a href="http://dx.doi.org/10.1186/1471-2105-12-134">10.1186/1471-2105-12-134</a> Abstract: <a href="http://www.biomedcentral.com/1471-2105/12/134/abstract">http://www.biomedcentral.com/1471-2105/12/134/abstract</a></li>
<li><strong>WEP: a high-performance analysis pipeline for whole-exome data&nbsp;</strong>http://www.biomedcentral.com/1471-2105/14/S7/S11</li>
<li><strong>DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.&nbsp;</strong>http://www.ncbi.nlm.nih.gov/pubmed/23657089</li>
<li><strong>GATK: a Toolkit for Genome Analysis&nbsp;</strong>http://www.broadinstitute.org/gatk/</li>
<li><strong>Metagenomics</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/</li>
<li><strong>RNASeq</strong>:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/</li>
<li><strong>Bioinformatics and Seq courses</strong>:&nbsp;http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html</li>
<li><strong>Variant Detection (Model organism) Advanced tutorial</strong> https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM</li>
<li><strong>Variant Detection Introductory tutorial</strong> https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI</li>
<li><strong>Microbial de novo Assembly for Illumina Data Introductory tutorial</strong> https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM</li>
<li><strong>RNAseq Differential Gene Expression Introductory tutorial</strong> https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y</li>
</ul>
<blockquote>
<p>" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ".&nbsp;</p>
</blockquote><p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/NGScourse/" rel="nofollow">http://chagall.med.cornell.edu/NGScourse/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>

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