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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38304?offset=270</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</guid>
	<pubDate>Tue, 25 Jul 2017 05:03:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33955/crocoblast-optimized-parallel-implementation-of-local-sequence-alignment-algorithms</link>
	<title><![CDATA[CrocoBLAST: Optimized parallel implementation of local sequence alignment algorithms]]></title>
	<description><![CDATA[<p><span>Local sequence alignment is a cornerstone of bioinformatics, allowing to compare the amino-acid sequences of different proteins, or the nucleotide sequences of different pieces of DNA. The Basic Local Alignment Search Tool (BLAST) has revolutionized the field of bioinformatics, and is currently implemented in all free and commercial bioinformatics packages. However, with the advent of Next Generation Sequencing (NGS) and the development of new sequencing techniques, the utility of traditional BLAST implementations is limited. CrocoBLAST combines the accuracy and general applicability of BLAST with computational efficiency, accessibility, and user experience, so that NGS data can be analyzed efficiently even when only modest computational resources are available.</span></p>
<p>https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</p><p>Address of the bookmark: <a href="https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST" rel="nofollow">https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</guid>
	<pubDate>Fri, 25 May 2018 09:29:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36800/genomemapper-simultaneous-alignment-of-short-reads-against-multiple-genomes</link>
	<title><![CDATA[GenomeMapper: Simultaneous alignment of short reads against multiple genomes]]></title>
	<description><![CDATA[GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. It can be used to align against multiple genomes simulanteously or against a single reference. If you are unsure which one is the appropriate GenomeMapper, you might want to use the latter

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768987/<p>Address of the bookmark: <a href="http://1001genomes.org/software/genomemapper.html" rel="nofollow">http://1001genomes.org/software/genomemapper.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</guid>
	<pubDate>Fri, 18 Dec 2020 02:09:44 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42405/caretta-%E2%80%93-a-multiple-protein-structure-alignment-and-feature-extraction-suite</link>
	<title><![CDATA[Caretta – A multiple protein structure alignment and feature extraction suite]]></title>
	<description><![CDATA[<h3>Caretta &ndash;&nbsp;a multiple protein structure alignment and feature extraction suite</h3>
<p><span>Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.&nbsp;</span></p><p>Address of the bookmark: <a href="http://www.bioinformatics.nl/caretta/" rel="nofollow">http://www.bioinformatics.nl/caretta/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34292/automatic-filtering-trimming-error-removing-and-quality-control-for-fastq-data</guid>
	<pubDate>Mon, 13 Nov 2017 05:10:23 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34292/automatic-filtering-trimming-error-removing-and-quality-control-for-fastq-data</link>
	<title><![CDATA[Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data]]></title>
	<description><![CDATA[<p><span>Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data</span><br><code>AfterQC</code><span>&nbsp;can simply go through all fastq files in a folder and then output three folders:&nbsp;</span><span>good</span><span>,&nbsp;</span><span>bad</span><span>&nbsp;and&nbsp;</span><span>QC</span><span>&nbsp;folders, which contains good reads, bad reads and the QC results of each fastq file/pair.</span><br><span>Currently it supports processing data from HiSeq 2000/2500/3000/4000, Nextseq 500/550, MiniSeq...and other&nbsp;</span><a href="http://support.illumina.com/help/SequencingAnalysisWorkflow/Content/Vault/Informatics/Sequencing_Analysis/CASAVA/swSEQ_mCA_FASTQFiles.htm">Illumina 1.8 or newer formats</a></p><p>Address of the bookmark: <a href="https://github.com/OpenGene/AfterQC" rel="nofollow">https://github.com/OpenGene/AfterQC</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34504/minion-gc-an-r-script-to-do-some-qc-on-minion-data</guid>
	<pubDate>Sun, 03 Dec 2017 15:19:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34504/minion-gc-an-r-script-to-do-some-qc-on-minion-data</link>
	<title><![CDATA[MinION_GC: An R script to do some QC on MinION data]]></title>
	<description><![CDATA[<p><span>Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out there: it takes about a minute to analyse a 4GB flowcell on my laptop.</span></p>
<p>https://github.com/roblanf/minion_qc</p><p>Address of the bookmark: <a href="https://github.com/roblanf/minion_qc" rel="nofollow">https://github.com/roblanf/minion_qc</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</guid>
	<pubDate>Tue, 08 May 2018 04:58:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36518/mix-combining-multiple-assemblies-from-ngs-data</link>
	<title><![CDATA[MIX: Combining multiple assemblies from NGS data]]></title>
	<description><![CDATA[<p>Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.</p>
<p>The Mix algorithm, approach and results were published in BMC bioinformatics :&nbsp;<a href="http://www.biomedcentral.com/1471-2105/14/S15/S16">http://www.biomedcentral.com/1471-2105/14/S15/S16</a>.</p><p>Address of the bookmark: <a href="https://github.com/cbib/MIX" rel="nofollow">https://github.com/cbib/MIX</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38598/zenbu-a-collaborative-omics-data-integration-and-interactive-visualization-system</guid>
	<pubDate>Fri, 04 Jan 2019 13:35:26 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38598/zenbu-a-collaborative-omics-data-integration-and-interactive-visualization-system</link>
	<title><![CDATA[ZENBU: a collaborative, omics data integration and interactive visualization system]]></title>
	<description><![CDATA[<p><span>ZENBU</span><span>&nbsp;</span><span>is a data integration, data analysis, and visualization system enhanced for RNAseq, ChipSeq, CAGE and other types of next-generation-sequence-tag (NGS) based data. ZENBU allows for novel data exploration through "on-demand" data processing and interactive linked-visualizations and is able to make many-views from the same primary sequence alignment data which users can uploaded from BAM, BED, GFF and tab-text files.&nbsp;<br>Please check our&nbsp;<a href="http://fantom.gsc.riken.jp/zenbu/wiki">documentation wiki</a>&nbsp;for details on how to use the system, or check out some of the views above.</span></p><p>Address of the bookmark: <a href="http://fantom.gsc.riken.jp/zenbu/" rel="nofollow">http://fantom.gsc.riken.jp/zenbu/</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39200/omtools-a-software-package-for-visualizing-and-processing-optical-mapping-data</guid>
	<pubDate>Fri, 29 Mar 2019 01:21:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39200/omtools-a-software-package-for-visualizing-and-processing-optical-mapping-data</link>
	<title><![CDATA[OMTools: a software package for visualizing and processing optical mapping data]]></title>
	<description><![CDATA[<p><span>OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses.</span></p>
<p><span><a href="https://github.com/TF-Chan-Lab/OMTools">https://github.com/TF-Chan-Lab/OMTools</a></span></p><p>Address of the bookmark: <a href="https://github.com/TF-Chan-Lab/OMTools" rel="nofollow">https://github.com/TF-Chan-Lab/OMTools</a></p>]]></description>
	<dc:creator>BioJoker</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats</guid>
	<pubDate>Tue, 18 Feb 2020 03:36:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats</link>
	<title><![CDATA[pbmm2:A minimap2 frontend for PacBio native data formats]]></title>
	<description><![CDATA[<p><em>pbmm2</em> is a SMRT C++ wrapper for <a href="https://github.com/lh3/minimap2">minimap2</a>'s C API. Its purpose is to support native PacBio in- and output, provide sets of recommended parameters, generate sorted output on-the-fly, and postprocess alignments. Sorted output can be used directly for polishing using GenomicConsensus, if BAM has been used as input to <em>pbmm2</em>. Benchmarks show that <em>pbmm2</em> outperforms BLASR in sequence identity, number of mapped bases, and especially runtime. <em>pbmm2</em> is the official replacement for BLASR.</p><p>Address of the bookmark: <a href="https://github.com/PacificBiosciences/pbmm2" rel="nofollow">https://github.com/PacificBiosciences/pbmm2</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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