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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43260?</link>
	<atom:link href="https://bioinformaticsonline.com/related/43260?" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<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/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</guid>
	<pubDate>Fri, 11 May 2018 05:07:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36533/mecat-fast-mapping-error-correction-and-de-novo-assembly-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads]]></title>
	<description><![CDATA[<p>MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>. MECAT performance were compared with&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>,&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>&nbsp;and&nbsp;<a href="http://canu.readthedocs.io/en/latest/">Canu(v1.3)</a>&nbsp;in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the&nbsp;<a href="http://cbcb.umd.edu/software/pbcr/mhap/">PBcR-Mhap pipeline</a>&nbsp;and&nbsp;<a href="https://github.com/PacificBiosciences/falcon">FALCON</a>.&nbsp;</p>
<p>https://www.nature.com/articles/nmeth.4432</p><p>Address of the bookmark: <a href="https://github.com/xiaochuanle/MECAT" rel="nofollow">https://github.com/xiaochuanle/MECAT</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</guid>
	<pubDate>Mon, 31 Jan 2022 07:18:16 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/43728/short-read-assembly-using-spades</link>
	<title><![CDATA[Short-read assembly using Spades !]]></title>
	<description><![CDATA[<h2 id="short-read-assembly-a-comparison">If we only had Illumina reads, we could also assemble these using the tool Spades.</h2><p>You can try this here, or try it later on your own data.</p><h2 id="get-data">Get data</h2><p>We will use the same Illumina data as we used above:</p><ul>
<li>illumina_R1.fastq.gz: the Illumina forward reads</li>
<li>illumina_R2.fastq.gz: the Illumina reverse reads</li>
</ul><h2 id="assemble">Assemble</h2><p>Run Spades:</p><div><pre>spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina
</pre></div><ul>
<li><code>-1</code>&nbsp;is input file of forward reads</li>
<li><code>-2</code>&nbsp;is input file of reverse reads</li>
<li><code>--careful</code>&nbsp;minimizes mismatches and short indels</li>
<li><code>--cov-cutoff auto</code>&nbsp;computes the coverage threshold (rather than the default setting, &ldquo;off&rdquo;)</li>
<li><code>-o</code>&nbsp;is the output directory</li>
</ul><h2 id="results">Results</h2><p>Move into the output directory and look at the contigs:</p><div><pre>infoseq contigs.fasta</pre></div>]]></description>
	<dc:creator>Abhimanyu Singh</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/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</guid>
	<pubDate>Mon, 10 Feb 2014 05:57:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/8265/list-of-generic-simulation-softwaretoolsresource-with-brief-description-and-homepage</link>
	<title><![CDATA[List of generic simulation software/tools/resource with brief description and homepage !!!]]></title>
	<description><![CDATA[<p>List of generic simulation software/tools/resource with brief description and homepage</p><p><img src="http://www.evolution-of-life.com/fileadmin/images/carousel/genetic.PNG" alt="image" style="border: 0px;"></p><p>ALF <br />A Simulation Framework for Genome Evolution <br />http://www.cbrg.ethz.ch/alf<br /><br />Bayesian Serial SimCoal <br />Bayesian Serial SimCoal, (BayeSSC) is a modification of SIMCOAL 1.0, a program written by Laurent Excoffier, John Novembre, and Stefan Schneider. <br />http://www.stanford.edu/group/hadlylab/ssc/index.html<br /><br />BEERS <br />BEERS was designed to benchmark RNA-Seq alignment algorithms and also algorithms that aim to reconstruct different isoforms and alternate splicing from RNA-Seq data <br />http://cbil.upenn.edu/beers/<br /><br />BOTTLENECK <br />Bottleneck is a program for detecting recent effective population size reductions from allele data frequencies <br />http://www.ensam.inra.fr/urlb/bottleneck/bottleneck.html<br /><br />BottleSim <br />BottleSim is a computer simulation program for simulating the process of population bottlenecks <br />http://chkuo.name/software/bottlesim.html<br /><br />CASS <br />Protein Sequence Simulation <br />http://www.wyomingbioinformatics.org/liberlesgroup/cass/<br /><br />CDPOP <br />CDPOP is a landscape genetics tool for simulating the emergence of spatial genetic structure in populations resulting from specified landscape processes governing organism movement behavior. <br />http://cel.dbs.umt.edu/cdpop<br /><br />CoalFace <br />CoalFace is a simulation of the coalescent process with the visual display of gene genealogies. <br />http://web.up.ac.za/default.asp?ipkcategoryid=3283<br /><br />CoaSim <br />CoaSim is a tool for simulating the coalescent process with recombination and geneconversion under various demographic models. <br />http://users-birc.au.dk/mailund/coasim/index.html<br /><br />cosi <br />The cosi package is written in C and is available as a tar file. <br />http://www.broadinstitute.org/~sfs/cosi/<br /><br />CS-PSeq-Gen <br />A program to simulate the evolution of protein sequences under the constraints of the information of a particular reconstructed phylogeny <br />http://bioserv.rpbs.univ-paris-diderot.fr/software/cs-pseq-gen.html<br /><br />DAWG <br />An application designed to simulate the evolution of recombinant DNA sequences in continuous time <br />http://scit.us/projects/dawg<br /><br />Easypop <br />EASYPOP is an individual based model intended to simulate datasets under a very broad range of conditions <br />http://www.unil.ch/dee/page36926_fr.html<br /><br />EggLib <br />EggLib is a C++/Python library and program package for evolutionary genetics and genomics. <br />http://egglib.sourceforge.net/<br /><br />EvolSimulator <br />A simulation test bed for hypotheses of genome evolution <br />http://acb.qfab.org/acb/evolsim/<br /><br />EvolveAGene <br />A realistic coding sequence simulation program that separates mutation from selection and allows the user to set selection conditions <br />http://bellinghamresearchinstitute.com/software/index.html<br /><br />fastsimcoal <br />A continuous-&not;‐time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios <br />http://cmpg.unibe.ch/software/fastsimcoal/<br /><br />FastSLINK <br />Simulation of Marker and Phenotype Data in Pedigrees <br />http://watson.hgen.pitt.edu/<br /><br />FFPopSim <br />C++/Python library for population genetics. <br />http://webdav.tuebingen.mpg.de/ffpopsim/<br /><br />FLUX SIMULATOR <br />The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters. <br />http://flux.sammeth.net/simulator.html<br /><br />ForSim <br />ForSim: A Forward Evolutionary Computer Simulation <br />http://www.anthro.psu.edu/weiss_lab/research.shtml<br /><br />ForwSim <br />The program given below is based on the algorithm described in Padhukasahasram et al. 2008 to simulate genetic drift in a standard Wright-Fisher process. <br />http://badri-populationgeneticsimulators.blogspot.com/<br /><br />FPG <br />Forward Population Genetic simulation <br />http://genfaculty.rutgers.edu/hey/software#fpg<br /><br />FREGENE <br />FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations. <br />http://www.ebi.ac.uk/projects/bargen/download/fregen/documentation_html.html<br /><br />GAMETES <br />Genetic Architecture Model Emulator for Testing and Evaluating Software: Simulates complex SNP models with pure, strict epistatic interactions with n-loci. <br />http://sourceforge.net/projects/gametes/?source=navbar<br /><br />GASP <br />Genometric Analysis Simulation Program. A software tool for testing and investigating methods in statistical genetics by generating samples of family data based on user specified models. <br />http://research.nhgri.nih.gov/gasp/<br /><br />GemSIM <br />Next generation sequencing read simulator <br />http://sourceforge.net/projects/gemsim/<br /><br />GeneArtisan <br />Simulation of Markers in Case-Control Study Designs <br />http://www.rannala.org/?page_id=241<br /><br />GENOME <br />A rapid coalescent-based whole genome simulator <br />http://www.sph.umich.edu/csg/liang/genome/<br /><br />GenomePop2 <br />GenomePop2 is a specialization of the program GenomePop just to manage SNPs under more flexible and useful settings. If you need models with more than 2 alleles please use the GenomePop program version. <br />http://webs.uvigo.es/acraaj/genomepop2.htm<br /><br />GenomeSimla <br />GenomeSIMLA is currently under development- however, we have a beta release that we are asking to be tested <br />http://chgr.mc.vanderbilt.edu/genomesimla/<br /><br />GENS2 <br />Simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. <br />https://sourceforge.net/projects/gensim/<br /><br />GWAsimulator <br />A rapid whole genome simulation program <br />http://biostat.mc.vanderbilt.edu/wiki/main/gwasimulator<br /><br />HAP-SAMPLE <br />An association simulator for candidate regions or genome scans <br />http://www.hapsample.org/<br /><br />HAPGEN <br />A simulator for the simulation of case control datasets at SNP markers <br />https://mathgen.stats.ox.ac.uk/genetics_software/hapgen/hapgen2.html<br /><br />HapSim <br />A simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients <br />http://cran.r-project.org/web/packages/hapsim/index.html<br /><br />HAPSIMU <br />A program that simulates heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model <br />http://l.web.umkc.edu/liujian/<br /><br />IBDsim <br />IBDSim is a computer package for the simulation of genotypic data under general isolation by distance models. <br />http://raphael.leblois.free.fr/<br /><br />indel-Seq-Gen <br />A biological sequence simulation program that simulates highly divergent DNA sequences and protein superfamilies <br />http://bioinfolab.unl.edu/~cstrope/isg/<br /><br />Indelible <br />A powerful and flexible simulator of biological evolution <br />http://abacus.gene.ucl.ac.uk/software/indelible/<br /><br />invertFREGENE <br />InvertFREGENE is a forward-in-time simulator of inversions in population genetic data <br />http://www.ebi.ac.uk/projects/bargen/<br /><br />kernalPop <br />A spatially explicit population genetic simulation engine <br />http://cran.r-project.org/src/contrib/archive/kernelpop/<br /><br />MaCS <br />Markovian Coalescent Simulator <br />http://www-hsc.usc.edu/~garykche/<br /><br />Mason <br />A package for the simulation of nucleotide data. <br />http://www.seqan.de/projects/mason/<br /><br />mbs <br />modifying Hudson's ms software to generate samples of DNA sequences with a biallelic site under selection <br />http://www.sendou.soken.ac.jp/esb/innan/innanlab/software.html<br /><br />Mendel's Accountant <br />Mendel's Accountant (MENDEL) is an advanced numerical simulation program for modeling genetic change over time and was developed collaboratively by Sanford, Baumgardner, Brewer, Gibson and ReMine <br />http://mendelsaccount.sourceforge.net/<br /><br />MetaSim <br />A tool to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets <br />http://ab.inf.uni-tuebingen.de/software/metasim/<br /><br />mlcoalsim <br />Multilocus Coalescent Simulations <br />http://code.google.com/p/mlcoalsim-v1/<br /><br />ms <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/source/mksamples.html<br /><br />msHOT <br />The purpose of this program is to allow one to investigate the statistical properties of such samples, to evaluate estimators or statistical tests, and generally to aid in the interpretation of polymorphism data sets. <br />http://home.uchicago.edu/~rhudson1/<br /><br />msms <br />A coalescent Simlation tool with selection. <br />http://www.mabs.at/ewing/msms/index.shtml<br /><br />MySSP <br />A program for the simulation of DNA sequence evolution across a phylogenetic tree <br />http://www.rosenberglab.net/software.php<br /><br />Nemo <br />A forward-time, individual-based, genetically explicit, and stochastic simulation program designed to study the evolution of genetic markers, life history traits, and phenotypic traits in a flexible (meta-)population framework. <br />http://nemo2.sourceforge.net/<br /><br />NetRecodon <br />Coalescent simulation of coding DNA sequences with recombination (inter and intracodon), migration and demography <br />http://code.google.com/p/netrecodon/<br /><br />PEDAGOG <br />Software for simulating eco-evolutionary population dynamics <br />https://bcrc.bio.umass.edu/pedigreesoftware/node/5<br /><br />phenosim <br />A tool to add phenotypes to simulated genotypes <br />http://evoplant.uni-hohenheim.de/doku.php?id=software:software<br /><br />PhyloSim <br />An R package for the Monte Carlo simulation of sequence evolution <br />http://bit.ly/rlsim-git<br /><br />pIRS <br />Profile-based Illumina pair-end reads simulator <br />https://code.google.com/p/pirs/<br /><br />ProteinEvolver <br />Simulation of protein evolution along phylogenies under structure-based substitution models <br />http://code.google.com/p/proteinevolver/<br /><br />QMSim <br />QTL and Marker Simulator <br />http://www.aps.uoguelph.ca/~msargol/qmsim/<br /><br />quantiNEMO <br />An individual-based program for the analysis of quantitative traits with explicit genetic architecture potentially under selection in a structured population <br />http://www2.unil.ch/popgen/softwares/quantinemo/<br /><br />RECOAL <br />Simulates new haplotype data from a reference population of haplotypes. <br />ftp://popgen.usc.edu/<br /><br />Recodon <br />Coalescent simulation of coding DNA sequences with recombination, migration and demography <br />http://code.google.com/p/recodon/<br /><br />rlsim <br />A package for simulating RNA-seq library preparation with parameter estimation <br />http://bit.ly/rlsim-git<br /><br />Rmetasim <br />Rmetasim is a front-end for the metasim engine that is implemented as a package that runs in the statistical computing environment R <br />http://linum.cofc.edu/software.html#metasim<br /><br />RNA Seq Simulator <br />RSS takes SAM alignment files from RNA-Seq data and simulates over dispersed, multiple replica, differential, non-stranded RNA-Seq datasets. <br />http://useq.sourceforge.net/cmdlnmenus.html#rnaseqsimulator<br /><br />Rose <br />Random model of sequence evolution <br />http://bibiserv.techfak.uni-bielefeld.de/rose/<br /><br />SelSim <br />SelSim is a program for Monte Carlo simulation of DNA polymorphism data for a recom- bining region within which a single bi-allelic site has experienced natural selection <br />http://www.well.ox.ac.uk/~spencer/selsim/<br /><br />Seq-Gen <br />An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees. <br />http://tree.bio.ed.ac.uk/software/seqgen/<br /><br />SEQPower <br />Statistical power analysis for sequence-based association studies <br />http://bioinformatics.org/spower/<br /><br />SeqSIMLA <br />SeqSIMLA can simulate sequence data with user-specified disease and quantitative trait models. Family or unrelated case-control data can be simulated. <br />http://seqsimla.sourceforge.net/<br /><br />Serial NetEvolve <br />A flexible utility for generating serially-sampled sequences along a tree or recombinant network <br />http://biorg.cis.fiu.edu/sne/<br /><br />SFS_CODE <br />SFS_CODE can perform forward population genetic simulations under a general Wright-Fisher model with arbitrary migration, demographic, selective, and mutational effects. <br />http://sfscode.sourceforge.net/sfs_code/index/index.html<br /><br />SIBSIM <br />Quantitative phenotype simulation in extended pedigrees <br />http://sourceforge.net/projects/sibsim/<br /><br />SIMCOAL2 <br />A coalescent program for the simulation of complex recombination patterns over large genomic regions under various demographic models <br />http://cmpg.unibe.ch/software/simcoal2/<br /><br />SimCopy <br />An R package simulating the evolution of copy number profiles along a tree. <br />http://bit.ly/simcopy<br /><br />SIMLA <br />SIMLA is a SIMuLAtion program that generates data sets of families for use in Linkage and Association studies. <br />http://www.chg.duke.edu/research/simla.html<br /><br />SimPed <br />A Simulation Program to Generate Haplotype and Genotype Data for Pedigree Structures <br />http://www.hgsc.bcm.tmc.edu/content/simped<br /><br />Simprot <br />A program to simulate protein evolution by substitution, insertion and deletion <br />http://www.uhnresearch.ca/labs/tillier/software.htm#3<br /><br />SimRare <br />Rare variant simulation and analysis tool <br />http://code.google.com/p/simrare/<br /><br />simuGWAS <br />A forward-time simulator that simulates realistic samples for genome-wide association studies. <br />http://simupop.sourceforge.net/cookbook/simucomplexdisease<br /><br />simuPOP <br />simuPOP is a general-purpose individual-based forward-time population genetics simulation environment. <br />http://simupop.sourceforge.net/<br /><br />SISSI <br />A software tool to generate data of related sequences along a given phylogeny, taking into account user defined system of neighbourhoods and instantaneous rate matrices. <br />http://www.cibiv.at/software/sissi/<br /><br />SNPsim <br />Coalescent simulation of hotspot recombination <br />http://code.google.com/p/phylosoftware/<br /><br />SPIP <br />SPIP simulates the transmission of genes from parents to offspring in a population having demographic structure defined by the user <br />http://swfsc.noaa.gov/textblock.aspx?division=fed&amp;id=3434<br /><br />Splatche <br />Spatial and Temporal Coalescences in Heterogeneous Environment <br />http://www.splatche.com/<br /><br />srv <br />Simulator of Rare Varaints (srv) is a simulator for the simulation of the introduction and evolution of (rare) genetic variants. <br />http://simupop.sourceforge.net/cookbook/simurarevariants<br /><br />SUP <br />SLINK/FastSLINK utility program <br />http://mlemire.freeshell.org/software.html<br /><br />TreesimJ <br />A flexible, forward-time population genetic simulator <br />http://code.google.com/p/treesimj/<br /><br />Vortex <br />VORTEX is an individual-based simulation model for population viability analysis (PVA). <br />http://www.vortex9.org/vortex.html<br /><br />References:</p><p>Image www.evolution-of-life.com</p><p>www.cancer.gov</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</guid>
	<pubDate>Thu, 24 Dec 2020 10:03:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads</link>
	<title><![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]></title>
	<description><![CDATA[<p><span>Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.</span></p><p>Address of the bookmark: <a href="https://github.com/chhylp123/hifiasm" rel="nofollow">https://github.com/chhylp123/hifiasm</a></p>]]></description>
	<dc:creator>Jit</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/43828/understanding-hifi-reads</guid>
	<pubDate>Thu, 24 Mar 2022 19:48:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</link>
	<title><![CDATA[Understanding HiFi Reads !]]></title>
	<description><![CDATA[<p><span>While little public data is available for either of the new synthetic long read approaches, Illumina showed an example comparison earlier this year at the&nbsp;</span><a href="https://www.festivalofgenomics.com/rami-mehio" target="_blank">Festival of Genomics &amp; Biodata conference</a><span>&nbsp;(FoG 2022). In the IGV screenshot presented (below), synthetic Infinity reads &ndash; labeled &ldquo;Longas&rdquo; &ndash; are at the top, followed by standard Illumina short reads, and PacBio HiFi reads labeled &ldquo;CCS&rdquo; depicted at the bottom:</span></p><p>Address of the bookmark: <a href="http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/" rel="nofollow">http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</guid>
	<pubDate>Tue, 08 May 2018 04:27:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads</link>
	<title><![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]></title>
	<description><![CDATA[<p><strong>HISAT2</strong><span>&nbsp;is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs&nbsp;</span><a href="http://dl.acm.org/citation.cfm?id=2674828">[Sir&eacute;n et al. 2014]</a><span>, we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).&nbsp;</span></p>
<p><span>more at&nbsp;https://ccb.jhu.edu/software/hisat2/index.shtml</span></p><p>Address of the bookmark: <a href="https://github.com/infphilo/hisat2" rel="nofollow">https://github.com/infphilo/hisat2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</guid>
	<pubDate>Wed, 15 Mar 2017 14:31:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/31566/software-and-tools-to-detect-structure-variation-with-long-reads</link>
	<title><![CDATA[Software and Tools to detect structure variation with long reads !!]]></title>
	<description><![CDATA[<p>Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio&nbsp;<em>de novo</em>&nbsp;assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.</p><p>With&nbsp;<span style="text-decoration: underline;"><a href="http://www.pacb.com/smrt-science/">Single Molecule, Real-Time (SMRT) Sequencing</a></span>, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:</p><ul>
<li>Uncover missing heritability linked to structural variation</li>
<li>Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease</li>
<li>Resolve structural variation across the complete size spectrum with basepair resolution</li>
</ul><p>Following are the SV tools, which can assist you to achieve your goal.</p><p><strong>Sniffles:</strong>&nbsp;Structural variation caller using third generation sequencing</p><p>Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!&nbsp;</p><p>More at&nbsp;https://github.com/fritzsedlazeck/Sniffles</p><p><strong style="font-size: 12.8px;"><br />MultiBreak-SV:</strong> It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.</p><p>There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.</p><p>More at&nbsp;https://github.com/raphael-group/multibreak-sv</p><p><strong style="font-size: 12.8px;"><br />Parliament:</strong>&nbsp;A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?</p><p>Publication about the algorithm and &ldquo;&hellip;the first long-read characterization of structural variation in a diploid human personal genome&hellip;&rdquo; (HS1011) -&nbsp;<a href="http://www.biomedcentral.com/1471-2164/16/286">&ldquo;Assessing structural variation in a personal genome&mdash;towards a human reference diploid genome&rdquo;</a></p><p>More at&nbsp;https://sourceforge.net/projects/parliamentsv/</p><p>https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf</p><p><br /><strong>PBHoney:</strong>&nbsp;the structural variation discovery tool&nbsp;<br /><br />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.</p><p>Read The Paper&nbsp;<a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a></p><p>More at&nbsp;https://sourceforge.net/projects/pb-jelly/</p><p><strong><br />SMRT-SV:</strong> Structural variant and indel caller for PacBio reads</p><p>Structural variant (SV) and indel caller for PacBio reads based on methods from&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>.</p><p>SMRT-SV provides an official software package for tools described in&nbsp;<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13907.html">Chaisson et al. 2014</a>&nbsp;and adds several key features including the following.</p><ul>
<li>Unified variant calling user interface with built-in cluster compute support</li>
<li>Small indel calling (2-49 bp)</li>
<li>Improved inversion calling (<code>screenInversions</code>)</li>
<li>Quality metric for SV calls based on number of local assemblies supporting each call</li>
<li>Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions</li>
<li>Genotyping of SVs with Illumina paired-end reads from WGS samples</li>
</ul><p>More at&nbsp;https://github.com/EichlerLab/pacbio_variant_caller</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
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