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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/28805?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26306/busco</guid>
	<pubDate>Sun, 07 Feb 2016 16:02:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26306/busco</link>
	<title><![CDATA[BUSCO]]></title>
	<description><![CDATA[<p>Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs</p>
<p>More at http://busco.ezlab.org/</p><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26332/pilon</guid>
	<pubDate>Mon, 08 Feb 2016 15:56:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26332/pilon</link>
	<title><![CDATA[Pilon]]></title>
	<description><![CDATA[<p>Pilon is a software tool which can be used to:</p>
<ul>
<li>Automatically improve draft assemblies</li>
<li>Find variation among strains, including large event detection</li>
</ul>
<p>Pilon requires as input a FASTA file of the genome along with one or more BAM files of reads aligned to the input FASTA file. Pilon uses read alignment analysis to identify inconsistencies between the input genome and the evidence in the reads. It then attempts to make improvements to the input genome, including:</p>
<ul>
<li>Single base differences</li>
<li>Small indels</li>
<li>Larger indel or block substitution events</li>
<li>Gap filling</li>
<li>Identification of local misassemblies, including optional opening of new gaps</li>
</ul>
<p>More at https://github.com/broadinstitute/pilon/wiki</p><p>Address of the bookmark: <a href="https://github.com/broadinstitute/pilon/wiki" rel="nofollow">https://github.com/broadinstitute/pilon/wiki</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</guid>
	<pubDate>Wed, 06 Apr 2016 05:25:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26906/paired-end-assembler-for-dna-sequences</link>
	<title><![CDATA[PAired-eND Assembler for DNA sequences]]></title>
	<description><![CDATA[<p>PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.</p>
<p>&nbsp;</p>
<p>More at https://github.com/neufeld/pandaseq</p><p>Address of the bookmark: <a href="https://github.com/neufeld/pandaseq" rel="nofollow">https://github.com/neufeld/pandaseq</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26925/reapr-a-universal-tool-for-genome-assembly-evaluation</guid>
	<pubDate>Wed, 06 Apr 2016 18:26:31 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26925/reapr-a-universal-tool-for-genome-assembly-evaluation</link>
	<title><![CDATA[REAPR: a universal tool for genome assembly evaluation]]></title>
	<description><![CDATA[<p>REAPR is a tool that evaluates the accuracy of a genome assembly using mapped paired end reads, without the use of a reference genome for comparison. It can be used in any stage of an assembly pipeline to automatically break incorrect scaffolds and flag other errors in an assembly for manual inspection. It reports mis-assemblies and other warnings, and produces a new broken assembly based on the error calls.</p>
<p>The software requires as input an assembly in FASTA format and paired reads mapped to the assembly in a BAM file. Mapping information such as the fragment coverage and insert size distribution is analysed to locate mis-assemblies. REAPR works best using mapped read pairs from a large insert library (at least 1000bp). Additionally, if a short insert Illumina library is also available, REAPR can combine this with the large insert library in order to score each base of the assembly.</p>
<p>http://www.sanger.ac.uk/science/tools/reapr</p><p>Address of the bookmark: <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-5-r47" rel="nofollow">https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-5-r47</a></p>]]></description>
	<dc:creator>Jitendra Prajapati</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</guid>
	<pubDate>Tue, 10 May 2016 07:46:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27257/busco-assessing-genome-assembly-and-annotation-completeness-with-benchmarking-universal-single-copy-orthologs</link>
	<title><![CDATA[BUSCO: Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs]]></title>
	<description><![CDATA[<ul>
<li><span>High-throughput genomics has revolutionized biological research, however, while the number of sequenced genomes grows by the day, quality assessment of the resulting assembled sequences remains complicated and mostly limited to technical measures like N50.&nbsp;</span></li>
<li></li>
<li><span>BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from&nbsp;</span><a href="http://orthodb.org/">OrthoDB</a><span>.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments are implemented in open-source software, with comprehensive lineage-specific sets of Benchmarking Universal Single-Copy Orthologs for arthropods, vertebrates, metazoans, fungi, eukaryotes, and bacteria.&nbsp;</span></li>
<li></li>
<li><span>These conserved orthologs are ideal candidates for large-scale phylogenomics studies, and the annotated BUSCO gene models built during genome assessments provide a comprehensive gene predictor training set for use as part of genome annotation pipelines.&nbsp;</span></li>
<li></li>
<li><span>BUSCO assessments offer intuitive metrics, based on evolutionarily informed expectations of gene content from hundreds of species, to gauge completeness of rapidly accumulating genomic data and satisfy an Iberian's quest for quality - "Busco calidad/qualidade".</span></li>
</ul><p>Address of the bookmark: <a href="http://busco.ezlab.org/" rel="nofollow">http://busco.ezlab.org/</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27328/platanus</guid>
	<pubDate>Fri, 13 May 2016 05:12:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27328/platanus</link>
	<title><![CDATA[Platanus]]></title>
	<description><![CDATA[<p>Platanus is a novel <em>de novo</em> sequence assembler that can reconstruct genomic sequences of<br> highly heterozygous diploids from massively parallel shotgun sequencing data.</p>
<p>The latest version is <a href="http://platanus.bio.titech.ac.jp/platanus/?page_id=14">1.2.4</a>.</p>
<p>To cite Platanus, please use the following:</p>
<p>Kajitani R, Toshimoto K, Noguchi H, Toyoda A, Ogura Y, Okuno M, Yabana M, Harada M, Nagayasu E, Maruyama H, Kohara Y, Fujiyama A, Hayashi T, Itoh T, &ldquo;Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads&rdquo;.&nbsp;Genome Res. 2014 Aug;24(8):1384-95. doi: 10.1101/gr.170720.113. [<a href="http://www.ncbi.nlm.nih.gov/pubmed/24755901">abstract</a> |<a href="http://genome.cshlp.org/content/24/8/1384.long"> full text</a>]</p><p>Address of the bookmark: <a href="http://platanus.bio.titech.ac.jp/" rel="nofollow">http://platanus.bio.titech.ac.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</guid>
	<pubDate>Fri, 24 Feb 2017 08:56:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31100/vaguevelvet-assembler-graphical-front-end</link>
	<title><![CDATA[VAGUE:Velvet Assembler Graphical Front End]]></title>
	<description><![CDATA[<p>VAGUE is a vague acronym for "Velvet Assembler Graphical Front End", which means it is a GUI for the Velvet <em>de novo</em> assembler. The command line version of Velvet can be complicated for beginners to use, but VAGUE makes it clear and simple</p>
<p>More at&nbsp;http://www.vicbioinformatics.com/software.vague.shtml</p><p>Address of the bookmark: <a href="http://www.vicbioinformatics.com/software.vague.shtml" rel="nofollow">http://www.vicbioinformatics.com/software.vague.shtml</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29957/record</guid>
	<pubDate>Fri, 25 Nov 2016 08:23:36 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29957/record</link>
	<title><![CDATA[RECORD]]></title>
	<description><![CDATA[<p>Background. Next-generation sequencing technologies are now producing multiple times the genome size in total reads from a single experiment. This is enough information to reconstruct at least some of the differences between the individual genome studied in the experiment and the reference genome of the species. However, in most typical protocols, this information is disregarded and the reference genome is used. Results. We provide a new approach that allows researchers to reconstruct genomes very closely related to the reference genome (e.g., mutants of the same species) directly from the reads used in the experiment. Our approach applies de novo assembly software to experimental reads and so-called pseudoreads and uses the resulting contigs to generate a modified reference sequence. In this way, it can very quickly, and at no additional sequencing cost, generate new, modified reference sequence that is closer to the actual sequenced genome and has a full coverage. In this paper, we describe our approach and test its implementation called RECORD. We evaluate RECORD on both simulated and real data. We made our software publicly available on sourceforge. Conclusion. Our tests show that on closely related sequences RECORD outperforms more general assisted-assembly software.</p>
<p>More at&nbsp;https://sourceforge.net/projects/record-genome-assembler/files/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pubmed/26558255" rel="nofollow">https://www.ncbi.nlm.nih.gov/pubmed/26558255</a></p>]]></description>
	<dc:creator>Bulbul</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30090/standardized-velvet-assembly-report</guid>
	<pubDate>Fri, 09 Dec 2016 03:59:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30090/standardized-velvet-assembly-report</link>
	<title><![CDATA[Standardized velvet assembly report]]></title>
	<description><![CDATA[<p>Requirements:</p>
<ul>
<li>velvet (velveth velvetg should be in your PATH)</li>
<li>R (with Sweave)</li>
<li>pdflatex (usually part of TeTeX)</li>
<li>ggplot2 (from R prompt type install.packages("ggplot2","proto","xtable"))</li>
<li>Perl</li>
</ul>
<p>Optional:</p>
<ul>
<li>BLAT or BLAST (to generate alignments against a reference genome). If using BLAT, add faToTwoBit,gfClient,gfServer to your PATH. If using BLAST, add blastall and formatdb.</li>
</ul>
<p>Edit permute.sh to your liking, paying particular attention to the kmer, cvCut, expCov, and other flags</p>
<p>To Run:</p>
<ol>
<li><code>perl fastaAllSize mysequences.fa &gt; mysequences.stat or gunzip -c mysequences.fa.gz | fastaAllSize &gt; mysequences.stat</code>&nbsp;Substitute fastqAllSize for fastq files.</li>
<li><code>./permute.sh mysequences</code>&nbsp;(leave out the .fa)</li>
</ol>
<p>https://github.com/leipzig/standardized-velvet-assembly-report</p><p>Address of the bookmark: <a href="https://github.com/leipzig/standardized-velvet-assembly-report" rel="nofollow">https://github.com/leipzig/standardized-velvet-assembly-report</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30130/scaffmatch</guid>
	<pubDate>Tue, 13 Dec 2016 10:23:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30130/scaffmatch</link>
	<title><![CDATA[ScaffMatch]]></title>
	<description><![CDATA[<p>caffMatch is a novel scaffolding tool based on Maximum-Weight Matching able to produce high-quality scaffolds from NGS data (reads and contigs). The tool is written in Python 2.7. It also includes a bash script wrapper that calls aligner in case one needs to first map reads to contigs (instead of providing .sam files).</p>
<p>The arguments accepted by ScaffMatch are:</p>
<p>&nbsp; -w) Working directory -- this is the directory where ScaffMatch files are stored. These are .sam files produced after mapping reads to contigs and the resulting scaffolds file `scaffolds.fa` fasta file;</p>
<p>&nbsp; -c) Contig fasta file;</p>
<p>&nbsp; -m) Command line argument with no options. It is used when .sam files are used instead of reads .fastq files. Do not use this option if you provide reads files;</p>
<p>&nbsp; -1) (Comma separated list of) either .fastq or .sam file(s) corresponding to the first read of the read pair;</p>
<p>&nbsp; -2) (Comma separated list of) either .fastq or .sam file(s) corresponding to the second read of the read pair;</p>
<p>&nbsp; -i) (Comma separated list of) insert size(s) of the library(-ies);</p>
<p>&nbsp; -s) (Comma separated list of) library(-ies) standard deviation(s) of insert size(s);</p>
<p>&nbsp; -t) Bundle threshold. Pairs of contigs supported by number of read pairs less than the value of this argument are discarded. Optional argument, by default it is equal to 5;</p>
<p>&nbsp; -g) Matching heuristics: use `max_weight` for Maximum Weight Matching heuristics with the Insertion step, use `backbone` for Maximum Weight Matching heuristics without the Insertion step, use `greedy` for Greedy Matching heuristics;</p>
<p>&nbsp; -l) Log file - where to store the logs. Optional argument. By default, stdout is used.</p><p>Address of the bookmark: <a href="http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch" rel="nofollow">http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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