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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37984?offset=120</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</guid>
	<pubDate>Thu, 14 Jun 2018 07:31:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36935/assemblytics-delta-file-to-analyze-alignments-of-an-assembly-to-another-assembly-or-a-reference-genome</link>
	<title><![CDATA[assemblytics: delta file to analyze alignments of an assembly to another assembly or a reference genome]]></title>
	<description><![CDATA[Download and install MUMmer
Align your assembly to a reference genome using nucmer (from MUMmer package)
$ nucmer -maxmatch -l 100 -c 500 REFERENCE.fa ASSEMBLY.fa -prefix OUT
Consult the MUMmer manual if you encounter problems

Optional: Gzip the delta file to speed up upload (usually 2-4X faster)
$ gzip OUT.delta
Then use the OUT.delta.gz file for upload.
Upload the .delta or delta.gz file (view example) to Assemblytics
Important: Use only contigs rather than scaffolds from the assembly. This will prevent false positives when the number of Ns in the scaffolded sequence does not match perfectly to the distance in the reference.

The unique sequence length required represents an anchor for determining if a sequence is unique enough to safely call variants from, which is an alternative to the mapping quality filter for read alignment.

http://assemblytics.com/<p>Address of the bookmark: <a href="http://assemblytics.com/" rel="nofollow">http://assemblytics.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37785/haplomerger2-rebuilding-both-haploid-sub-assemblies-from-high-heterozygosity-diploid-genome-assembly</guid>
	<pubDate>Thu, 27 Sep 2018 07:08:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37785/haplomerger2-rebuilding-both-haploid-sub-assemblies-from-high-heterozygosity-diploid-genome-assembly</link>
	<title><![CDATA[HaploMerger2: rebuilding both haploid sub-assemblies from high-heterozygosity diploid genome assembly]]></title>
	<description><![CDATA[<p><span><span>HM2 can process any diploid assemblies, but it is especially suitable for diploid assemblies with high heterozygosity (&ge;3%), which can be difficult for other tools. This pipeline also implements flexible and sensitive assembly error detection, a hierarchical scaffolding procedure and a reliable gap-closing method for haploid sub-assemblies.</span></span></p>
<p><span>Source code, executables and the testing dataset are freely available at&nbsp;</span><a href="https://github.com/mapleforest/HaploMerger2/releases/" target="">https://github.com/mapleforest/HaploMerger2/releases/</a><span>.</span></p><p>Address of the bookmark: <a href="https://github.com/mapleforest/HaploMerger2/releases/" rel="nofollow">https://github.com/mapleforest/HaploMerger2/releases/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</guid>
	<pubDate>Sun, 04 Nov 2018 16:44:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores</link>
	<title><![CDATA[Referee: Genome assembly quality scores]]></title>
	<description><![CDATA[<p>Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.</p>
<p>We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.</p>
<h3>Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.</h3>
<p>https://github.com/gwct/referee</p><p>Address of the bookmark: <a href="https://gwct.github.io/referee/#" rel="nofollow">https://gwct.github.io/referee/#</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</guid>
	<pubDate>Mon, 21 Jan 2019 17:58:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38755/svaba-genome-wide-detection-of-structural-variants-and-indels-by-local-assembly</link>
	<title><![CDATA[SvABA: Genome-wide detection of structural variants and indels by local assembly]]></title>
	<description><![CDATA[<p><span>SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of&nbsp;</span><a href="https://github.com/jts/sga">SGA</a><span>&nbsp;(String Graph Assembler) by Jared Simpson, and&nbsp;</span><a href="https://github.com/lh3/bwa">BWA-MEM</a><span>&nbsp;by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using&nbsp;</span><a href="https://github.com/walaj/VariantBam">VariantBam</a><span>&nbsp;rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.</span></p><p>Address of the bookmark: <a href="https://github.com/walaj/svaba" rel="nofollow">https://github.com/walaj/svaba</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</guid>
	<pubDate>Fri, 01 Feb 2019 11:55:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/file/view/38886/evaluation-of-genome-assembly-software-based-on-long-reads</link>
	<title><![CDATA[Evaluation of genome assembly software based on long reads]]></title>
	<description><![CDATA[<p>TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.</p><p>In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads</p>]]></description>
	<dc:creator>BioStar</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/38886" length="382699" type="application/pdf" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39253/gmass-a-novel-measure-for-genomeassembly-structural-similarity</guid>
	<pubDate>Sun, 14 Apr 2019 20:35:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39253/gmass-a-novel-measure-for-genomeassembly-structural-similarity</link>
	<title><![CDATA[GMASS: a novel measure for genomeassembly structural similarity]]></title>
	<description><![CDATA[<div id="Abstract">
<div id="ASec3">
<p id="Par3">The GMASS score is a novel measure for representing structural similarity between two assemblies. It will contribute to the understanding of assembly output and developing de novo assemblers.</p>
<p><a href="https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z">https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z</a></p>
</div>
</div><p>Address of the bookmark: <a href="http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php" rel="nofollow">http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41397/svaba-structural-variation-and-indel-detection-by-local-assembly</guid>
	<pubDate>Tue, 10 Mar 2020 07:52:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41397/svaba-structural-variation-and-indel-detection-by-local-assembly</link>
	<title><![CDATA[SvABA: Structural variation and indel detection by local assembly]]></title>
	<description><![CDATA[<p><span>SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of&nbsp;</span><a href="https://github.com/jts/sga">SGA</a><span>&nbsp;(String Graph Assembler) by Jared Simpson, and&nbsp;</span><a href="https://github.com/lh3/bwa">BWA-MEM</a><span>&nbsp;by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using&nbsp;</span><a href="https://github.com/walaj/VariantBam">VariantBam</a><span>&nbsp;rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.</span></p><p>Address of the bookmark: <a href="https://github.com/walaj/svaba" rel="nofollow">https://github.com/walaj/svaba</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</guid>
	<pubDate>Fri, 01 May 2020 03:00:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41592/refka-a-fast-and-efficient-long-read-genome-assembly-approach-for-large-and-complex-genomes</link>
	<title><![CDATA[RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes]]></title>
	<description><![CDATA[<p><span>RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/AppliedBioinformatics/RefKA" rel="nofollow">https://github.com/AppliedBioinformatics/RefKA</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26309/ratt</guid>
	<pubDate>Sun, 07 Feb 2016 16:09:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26309/ratt</link>
	<title><![CDATA[RATT]]></title>
	<description><![CDATA[<p><strong>RATT</strong> is software to transfer annotation from a reference (annotated) genome to an unannotated query genome.</p>
<p>It was first developed to transfer annotations between different genome assembly versions. However, it can also transfer annotations between strains and even different species, like <em>Plasmodium chabaudi</em> onto <em> P. berghei</em>, between different Leishmania species or <em>Salmonella enterica</em> onto other Salmonella serotypes. <strong>RATT</strong> is able to transfer any entries present on a reference sequence, such as the systematic id or an annotator's notes; such information would be lost in a <em>de novo</em> annotation.</p>
<p>More at http://ratt.sourceforge.net/</p><p>Address of the bookmark: <a href="http://ratt.sourceforge.net/" rel="nofollow">http://ratt.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</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>

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