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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30242?offset=180</link>
	<atom:link href="https://bioinformaticsonline.com/related/30242?offset=180" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27806/blobology</guid>
	<pubDate>Mon, 13 Jun 2016 10:18:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27806/blobology</link>
	<title><![CDATA[Blobology]]></title>
	<description><![CDATA[<p><span>Tools for making blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step</span></p>
<p>Blaxter Lab, Institute of Evolutionary Biology, University of Edinburgh</p>
<p><span>Goal</span>: To create blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step.</p>
<p>This repository accompanies the paper:<br><span>Blobology: exploring raw genome data for contaminants, symbionts and parasites using taxon-annotated GC-coverage plots.</span>&nbsp;<em>Sujai Kumar, Martin Jones, Georgios Koutsovoulos, Michael Clarke, Mark Blaxter</em><br>(submitted 2013-10-01 to&nbsp;<em>Frontiers in Bioinformatics and Computational Biology special issue : Quality assessment and control of high-throughput sequencing data</em>).</p>
<p>It contains bash/perl/R scripts for running the analysis presented in the paper to create a preliminary assembly, and to create and collate GC content, read coverage and taxon annotation for the preliminary assembly, which can be visualised, such as Figure 2a from the paper showing TAGC plots/blobplots for&nbsp;<em>Caenorhabditis</em>&nbsp;sp. 5:&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/blaxterlab/blobology" rel="nofollow">https://github.com/blaxterlab/blobology</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29995/hga</guid>
	<pubDate>Tue, 29 Nov 2016 07:25:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29995/hga</link>
	<title><![CDATA[HGA]]></title>
	<description><![CDATA[<p>HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler (Velvet or SPAdes in this version) and using a given kmer size. 3. Merging all the assemblies of the partition. 4. Combining all the assemblies of the partition (using velvet with kmer value of 31). 5. Finaly, re-assembling the whole dataset with the merged contigs or the combined contigs, using a given kmer size.</p>
<p>https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA</p><p>Address of the bookmark: <a href="https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA" rel="nofollow">https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</guid>
	<pubDate>Sun, 02 Apr 2017 14:31:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32011/fools-guide</link>
	<title><![CDATA[Fools guide]]></title>
	<description><![CDATA[<p><span>This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.</span></p>
<p>http://sfg.stanford.edu/denovo.html</p>
<p>http://sfg.stanford.edu/sequencing.html</p>
<p>http://sfg.stanford.edu/BLAST.html</p>
<p>http://sfg.stanford.edu/denovo.html&nbsp;</p><p>Address of the bookmark: <a href="http://sfg.stanford.edu/guide.html" rel="nofollow">http://sfg.stanford.edu/guide.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</guid>
	<pubDate>Mon, 10 Apr 2017 04:45:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2</link>
	<title><![CDATA[WGS Celera Assembler version 8.3rc2]]></title>
	<description><![CDATA[<p>These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.<br><br>This distribution package provides a stable, tested, documented version of the software.&nbsp; The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.<br><br>The source code package includes full source code (revision 4627), Makefiles, and scripts.&nbsp; A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.&nbsp; This distribution includes [http://samtools.sourceforge.net/ SAMtools], [http://www.cbcb.umd.edu/software/jellyfish/ Jellyfish 2.0], [https://github.com/pbjd/pbutgcns PBUTGCNS], [https://github.com/PacificBiosciences/pbdagcon PBDAGCON], [https://github.com/PacificBiosciences/BLASR BLASR], and parts of the [https://github.com/PacificBiosciences/FALCON/tree/v0.1.3 Falcon assembler].<br><br>Full documentation can be found online at http://wgs-assembler.sourceforge.net/.</p>
<p>Interesting scripts within it</p>
<p>urbe@urbo214b[bin] ls&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; []<br>-rwxrwxr-x 1 urbe urbe&nbsp; 11K Apr 10 11:41 addCNSToStore<br>-rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs<br>-rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest<br>-rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds<br>-rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta<br>-rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics<br>-rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl<br>-rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr<br>-rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart<br>-rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus<br>-rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness<br>-rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap<br>-rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs<br>-rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:41 ca2ace.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 12K Apr 10 11:41 caqc_help.ini<br>-rwxrwxr-x 1 urbe urbe&nbsp; 61K Apr 10 11:41 caqc.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 23K Apr 10 11:41 cat-corrects<br>-rwxrwxr-x 1 urbe urbe&nbsp; 24K Apr 10 11:41 cat-erates<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump<br>-rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera<br>-rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply<br>-rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise<br>-rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 convertOverlap<br>-rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 20K Apr 10 11:41 convertToPBCNS<br>-rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags<br>-rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps<br>-rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio<br>-rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns<br>-rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate<br>-rwxrwxr-x 1 urbe urbe&nbsp; 37K Apr 10 11:41 demotePosMap<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons<br>-rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate<br>-rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold<br>-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition<br>-rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages<br>-rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense<br>-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA<br>-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze<br>-rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample<br>-rwxrwxr-x 1 urbe urbe&nbsp; 62K Apr 10 11:40 fastqSimulate<br>-rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort<br>-rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA<br>-rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap<br>-rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim<br>-rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth<br>-rwxrwxr-x 1 urbe urbe&nbsp; 29K Apr 10 11:41 fragsInVars<br>-rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones<br>-rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench<br>-rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate<br>-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ<br>-rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling<br>-rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM<br>-rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim<br>-rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish<br>-rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique<br>-rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique<br>-rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy<br>-rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl<br>-rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim<br>-rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply<br>-rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl<br>-rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds<br>-rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout<br>-rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore<br>-rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats<br>-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer<br>-rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe&nbsp; 33K Apr 10 11:41 overlapStoreIndexer<br>-rwxrwxr-x 1 urbe urbe&nbsp; 48K Apr 10 11:41 overlapStoreSorter<br>-rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry<br>lrwxrwxrwx 1 urbe urbe&nbsp;&nbsp;&nbsp; 4 Apr 10 11:41 pacBioToCA -&gt; PBcR<br>-rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR<br>-rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon<br>-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns<br>-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment<br>-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap<br>-rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq<br>-rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap<br>-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates<br>-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache<br>-rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 88K Apr 10 11:41 runCA-dedupe<br>-rwxrwxr-x 1 urbe urbe&nbsp; 14K Apr 10 11:41 runCA-overlapStoreBuild<br>-rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh<br>-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 13K Apr 10 11:40 show-corrects<br>-rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs<br>-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator<br>drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR<br>-rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracearchiveToCA<br>-rwxrwxr-x 1 urbe urbe&nbsp; 35K Apr 10 11:41 tracedb-to-frg.pl<br>-rwxrwxr-x 1 urbe urbe&nbsp; 44K Apr 10 11:41 trimFastqByQVWindow<br>-rwxrwxr-x 1 urbe urbe&nbsp; 18K Apr 10 11:40 uidclient<br>-rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v8-to-v9<br>-rwxrwxr-x 1 urbe urbe&nbsp; 42K Apr 10 11:40 upgrade-v9-to-v10<br>-rwxrwxr-x 1 urbe urbe&nbsp; 854 Apr 10 11:41 utg2fasta<br>-rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns<br>-rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix<br><br><br></p><p>Address of the bookmark: <a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page" rel="nofollow">http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</guid>
	<pubDate>Fri, 12 May 2017 10:50:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32633/a-post-assembly-genome-improvement-toolkit-pagit-to-obtain-annotated-genomes-from-contigs</link>
	<title><![CDATA[A Post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs]]></title>
	<description><![CDATA[<p>PAGIT addresses the need for software to generate high quality draft genomes. It is based on a series of programs that we developed:</p>
<p><a href="https://sourceforge.net/projects/abacas/files/">ABACAS</a>, that is able to contiguate contigs from a de novo assembly against a closely related reference.</p>
<p><a href="https://sourceforge.net/projects/image2/files/">IMAGE</a>, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.</p>
<p><a href="http://icorn.sourceforge.net/">iCORN</a>, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found&nbsp;<a href="ftp://ftp.sanger.ac.uk/pub4/resources/software/pagit/ICORN2/icorn2.V0.95.tgz">here</a>.</p>
<p><a href="https://ratt.svn.sourceforge.net/svnroot/ratt">RATT</a>, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.</p>
<p>PAGIT bundles these software and makes them more accessible for users.</p><p>Address of the bookmark: <a href="http://www.sanger.ac.uk/science/tools/pagit" rel="nofollow">http://www.sanger.ac.uk/science/tools/pagit</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</guid>
	<pubDate>Tue, 07 Nov 2017 04:36:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads</link>
	<title><![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]></title>
	<description><![CDATA[<p><span>We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast&nbsp;</span><em>Pichia stipitis</em><span>. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the&nbsp;</span><em>k</em><span>-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by &sim;280 bp or &sim;3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</guid>
	<pubDate>Tue, 08 May 2018 04:39:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36514/evidentialgene-tr2aacds-mrna-transcript-assembly-software</link>
	<title><![CDATA[EvidentialGene: tr2aacds, mRNA Transcript Assembly Software]]></title>
	<description><![CDATA[<p><span>EvidentialGene is a genome informatics project, "Evidence Directed Gene Construction for Eukaryotes", to construct high quality, accurate gene sets for animals and plants, developed by Don Gilbert at Indiana University, see</span><br><a href="http://arthropods.eugenes.org/EvidentialGene/" target="_blank">http://arthropods.eugenes.org/EvidentialGene/<span></span></a><br><br><span>Construction refers to the combination of classical gene prediction, and more recent gene assembly (de-novo and genome-assisted) methods. The basic Evigene methods involve using available best-of-breed gene prediction and assembly software, combining all evidence for genes, from expressed sequences, genome assembly sequences, related species protein sequences, and any other, to annotate and score gene constructions. Over-produced constructions are classified by gene evidence for best qualities per "locus", including genome-aligned and gene-transcript aligned (genome-free) locus identification. All software developed for EvidentialGene is publicly available. See project wiki/blog for notes.</span></p>
<p><span>Download&nbsp;</span></p>
<p>http://arthropods.eugenes.org/EvidentialGene/trassembly.html</p>
<p>https://sourceforge.net/p/evidentialgene/blog/</p><p>Address of the bookmark: <a href="http://arthropods.eugenes.org/EvidentialGene/trassembly.html" rel="nofollow">http://arthropods.eugenes.org/EvidentialGene/trassembly.html</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</guid>
	<pubDate>Mon, 14 May 2018 05:25:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36597/gappadder-a-sensitive-approach-for-closing-gaps-on-draft-genomes-with-short-sequence-reads</link>
	<title><![CDATA[GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads]]></title>
	<description><![CDATA[<p><span>This software is provided ``as is&rdquo; without warranty of any kind. In no event shall the author be held responsible for any damage resulting from the use of this software. The program package, including source codes, executables, and this documentation, is distributed free of charge. If you use this program in a publication, please cite the following reference:</span><br><span>Chong Chu, Xin Li, and Yufeng Wu. "GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads." bioRxiv (2017): 125534.</span></p><p>Address of the bookmark: <a href="https://github.com/Reedwarbler/GAPPadder" rel="nofollow">https://github.com/Reedwarbler/GAPPadder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</guid>
	<pubDate>Mon, 11 Jun 2018 05:43:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36897/gmcloser-closing-gaps-in-assemblies-accurately-with-a-likelihood-based-selection-of-contig-or-long-read-alignments</link>
	<title><![CDATA[GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments]]></title>
	<description><![CDATA[GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency.

https://academic.oup.com/bioinformatics/article/31/23/3733/209212<p>Address of the bookmark: <a href="https://academic.oup.com/bioinformatics/article/31/23/3733/209212" rel="nofollow">https://academic.oup.com/bioinformatics/article/31/23/3733/209212</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</guid>
	<pubDate>Wed, 27 Dec 2017 20:47:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/34916/bioinformatics-tools-developed-for-oxford-nanopore-data-analysis</link>
	<title><![CDATA[Bioinformatics tools developed for Oxford Nanopore data analysis !]]></title>
	<description><![CDATA[<p><span>MinION is the only portable real-time device for DNA and RNA&nbsp;</span><span>sequencing</span><span>. Each consumable flow cell can now generate 10&ndash;20 Gb of DNA&nbsp;</span><span>sequence</span><span>&nbsp;data. Ultra-</span><span>long read lengths are possible (hundreds of kb) as you can choose your fragment length.&nbsp;</span>One of the technical advantages of ONT data is the read length, which offers great prospects for genome assembly. Generally, assemblers are based on several different types of algorithms, such as greedy, overlap-layout-consensus (OLC), de Bruijn graph (DBG), and string graph.</p><p><span>List of analysis tools developed for Oxford Nanopore data</span></p><p>BWA <br />Fast nanopore data tuned alignment tool <br />https://github.com/lh3/bwa</p><p>GraphMap<br />Mapper for long and error-prone reads<br />https://github.com/isovic/graphmap</p><p>LAST<br />Nanopore tuned alignment tool<br />http://last.cbrc.jp/</p><p>LINKS<br />Software tool for long read scaffolding <br />https://github.com/warrenlr/LINKS/</p><p>marginAlign<br />Tools to align nanopore reads to a reference<br />https://github.com/benedictpaten/marginAlign</p><p>minoTour<br />Real time analysis tools<br />http://minotour.nottingham.ac.uk/</p><p>nanoCORR<br />Error-correction tool for nanopore sequence data<br />https://github.com/jgurtowski/nanocorr</p><p>NanoOK<br />Software for nanopore data, quality and error profiles<br />https://documentation.tgac.ac.uk/display/NANOOK/NanoOK</p><p>Nanopolish<br />Nanopore analysis and genome assembly software<br />https://github.com/jts/nanopolish</p><p>nanopore<br />Variant-detection tool for nanopore sequence data<br />https://github.com/mitenjain/nanopore</p><p>Nanocorrect<br />Error-correction tool for nanopore sequence data<br />https://github.com/jts/nanocorrect/</p><p>npReader<br />Real-time conversion and analysis of nanopore reads<br />https://github.com/mdcao/npReader</p><p>poRe<br />Tool for analyzing and visualizing nanopore data<br />https://sourceforge.net/p/rpore/wiki/Home/</p><p>PoreSeq<br />Error-correction and variant-calling software<br />https://github.com/tszalay/poreseq</p><p>Poretools<br />Nanopore sequence analysis and visualization software <br />https://github.com/arq5x/poretools</p><p>SSPACE-LongRead<br />Genome scaffolding tool <br />http://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE-longread</p><p>SMIS<br />Genome scaffolding tool <br />https://sourceforge.net/projects/phusion2/files/smis/</p><p>&nbsp;</p><p>List of assemblers for Oxford Nanopore MinION long reads</p><p>LQS<br />DALIGNER, Celera OLC Nanocorrect, <br />Nanopolish corrector<br />https://github.com/jts/nanopolish</p><p>PBcR<br />HGAP or BLASR, Celera OLC <br />PBcR corrector<br />http://wgs-assembler.sourceforge.net/wiki/index.php/PBcR<br /> &ndash;<br />Canu<br />MHAP, Celera OLC <br />Canu corrector<br />https://github.com/marbl/canu</p><p>Falcon<br />String graph, Celera OLC <br />Falcon corrector<br />https://github.com/PacificBiosciences/falcon</p><p>Miniasm <br />OLC<br />https://github.com/lh3/miniasm</p><p>ra-integrate<br />OLC<br />https://github.com/mariokostelac/ra-integrate/</p><p>ALLPATHS-LG<br />de Bruijn graph <br />ALLPATHS-L corrector<br />https://www.broadinstitute.org/software/allpaths-lg/blog/?page_id=12</p><p>SPAdes <br />de Bruijn graph <br />SPAdes corrector<br />http://bioinf.spbau.ru/spades</p>]]></description>
	<dc:creator>biogeek</dc:creator>
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