<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/43770?offset=70</link>
	<atom:link href="https://bioinformaticsonline.com/related/43770?offset=70" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</guid>
	<pubDate>Wed, 06 Dec 2017 02:08:14 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34528/cope-an-accurate-k-mer-based-pair-end-reads-connection-tool-to-facilitate-genome-assembly</link>
	<title><![CDATA[COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly]]></title>
	<description><![CDATA[<p><span>An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30&times; simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.</span></p><p>Address of the bookmark: <a href="ftp://ftp.genomics.org.cn/pub/cope" rel="nofollow">ftp://ftp.genomics.org.cn/pub/cope</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</guid>
	<pubDate>Sat, 16 Dec 2017 17:37:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/34685/tools-for-bacterial-whole-genome-annotation</link>
	<title><![CDATA[Tools for bacterial whole genome annotation]]></title>
	<description><![CDATA[<p><a href="http://rast.nmpdr.org/">RAST</a>&nbsp;&ndash;&nbsp;Web tool (upload contigs), uses the subsystems in the SEED database and&nbsp;provides detailed annotation and pathway analysis. Takes several hours per genome but I think this is the best way to get a high quality annotation (if you have only a few genomes to annotate).</p><p><a href="http://www.vicbioinformatics.com/software.prokka.shtml">Prokka</a>&nbsp;&ndash;&nbsp;Standalone command line tool, takes just a few minutes per genome.&nbsp;This is the best way to get good quality annotation in a flash, which is particularly useful if you have loads of genomes or need to annotate a pangenome or metagenome. Note however that the quality of functional information is not as good as RAST, and you&nbsp;will need several extra steps if you want to do&nbsp;functional profiling and pathway analysis of your genome(s)&hellip; which is in-built in RAST.</p><p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p><p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p><p><a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/">PGAP</a>: NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume.&nbsp; NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p><p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC453985">BEACON</a> (automated tool for Bacterial GEnome Annotation ComparisON), a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at:&nbsp;<a href="http://www.cbrc.kaust.edu.sa/BEACON/" target="pmc_ext">http://www.cbrc.kaust.edu.sa/BEACON/</a>.</p><p><a href="http://www.kegg.jp/blastkoala/">BlastKOLA</a>: Assigns K numbers to the user's sequence data by BLAST searches, respectively, against a nonredundant set of KEGG GENES. KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to this server and can be executed in an interactive mode. BlastKOALA is suitable for annotating fully sequenced genomes.</p><p><a href="http://www.sanger.ac.uk/science/tools/pagit">PAGIT</a>: Provides a toolkit for improving the quality of genome assemblies created via an assembly software. PAGIT compiled four tools: (i) ABACAS which classifies and orientates contigs and estimates the sizes of gaps between them; (ii) IMAGE uses paired-end reads to extend contigs and close gaps within the scaffolds; (iii) ICORN for identifying and correcting small errors in consensus sequences and; (iv) RATT for help annotation. The software was mainly created to analyze parasite genomes of up to about 300 Mb.</p><p><a href="http://www.yandell-lab.org/software/maker.html">MAKER: </a>A portable and easily configurable genome annotation pipeline. MAKER allows smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. It identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER's inputs are minimal and its ouputs can be directly loaded into a Generic Model Organism Database (GMOD). They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER is available for download and can be tested online via the MAKER Web Annotation Service (MWAS).</p><p><a href="https://www.sciencedirect.com/science/article/pii/S0167701215001207">MyPro</a> is a software pipeline for high-quality prokaryotic genome assembly and annotation. It was validated on 18 oral streptococcal strains to produce submission-ready, annotated draft genomes. MyPro installed as a virtual machine and supported by updated databases will enable biologists to perform quality prokaryotic genome assembly and annotation with ease.</p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</guid>
	<pubDate>Wed, 10 Jan 2018 03:10:45 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35131/giggle-a-search-engine-for-large-scale-integrated-genome-analysis</link>
	<title><![CDATA[GIGGLE: a search engine for large-scale integrated genome analysis]]></title>
	<description><![CDATA[<p><span>GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (</span><a href="https://github.com/ryanlayer/giggle">https://github.com/ryanlayer/giggle</a><span>) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.</span></p>
<p>https://www.nature.com/articles/nmeth.4556</p><p>Address of the bookmark: <a href="https://github.com/ryanlayer/giggle" rel="nofollow">https://github.com/ryanlayer/giggle</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</guid>
	<pubDate>Tue, 18 Feb 2020 07:43:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41158/carefully-opt-for-human-reference-genome</link>
	<title><![CDATA[Carefully opt for human reference genome]]></title>
	<description><![CDATA[<p><a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" target="_blank">Heng Li posted several issues with the human reference genomes given in these resources</a> and suggests the following compressed FASTA file to be used as hg38/GRCh38 human reference genome.</p>
<p>if you map reads to GRCh38 or hg38, use the following:</p>
<div>
<div>
<pre><code>ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz
</code></pre>
</div>
</div>
<p>There are several other versions of GRCh37/GRCh38. What&rsquo;s wrong with them? Here are a collection of potential issues:</p>
<p>More at http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</p><p>Address of the bookmark: <a href="http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use" rel="nofollow">http://lh3.github.io/2017/11/13/which-human-reference-genome-to-use</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</guid>
	<pubDate>Tue, 08 May 2018 04:52:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36516/metassembler-merging-and-optimizing-de-novo-genome-assemblies</link>
	<title><![CDATA[Metassembler: merging and optimizing de novo genome assemblies]]></title>
	<description><![CDATA[<p><span>Metassembler combines multiple whole genome de novo assemblies into a combined consensus assembly using the best segments of the individual assemblies.</span></p>
<p><span><span>Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence.&nbsp;</span></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/metassembler/?source=directory" rel="nofollow">https://sourceforge.net/projects/metassembler/?source=directory</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</guid>
	<pubDate>Mon, 04 Jun 2018 05:26:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36861/eagler-a-scaffolding-tool-for-long-reads</link>
	<title><![CDATA[EAGLER: a scaffolding tool for long reads.]]></title>
	<description><![CDATA[<p>EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.</p>
<p>The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:</p>
<ul>
<li>Mac OS X 10.11.1</li>
<li>Mac OS X 10.10.3</li>
<li>Ubuntu 14.04 LTS</li>
</ul>

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf<p>Address of the bookmark: <a href="https://github.com/mculinovic/EAGLER" rel="nofollow">https://github.com/mculinovic/EAGLER</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/file/view/36945/download-blasr-13-version</guid>
	<pubDate>Fri, 15 Jun 2018 03:01:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/file/view/36945/download-blasr-13-version</link>
	<title><![CDATA[Download blasr 1.3 version]]></title>
	<description><![CDATA[<p>DOWNLOAD LINK: https://github.com/BioInf-Wuerzburg/proovread/raw/master/util/blasr-1.3.1/blasr</p><p>I'm running "OPERA-LG_v2.0.5/bin/preprocess_reads.pl" and have the following error:</p><p>fail to open file './temporarySam'</p><p><br />[bwa_aln_core] write to the disk... 0.09 sec<br />[bwa_aln_core] 70778880 sequences have been processed.<br />[bwa_aln_core] calculate SA coordinate... 161.35 sec<br />[bwa_aln_core] write to the disk... 0.06 sec<br />[bwa_aln_core] 70989574 sequences have been processed.<br />[main] Version: 0.7.15-r1140<br />[main] CMD: bwa aln -t 30 all_p_ctg.fa -<br />[main] Real time: 2402.523 sec; CPU: 53429.488 sec<br />[E::hts_open_format] Failed to open file temporarySam<br />samtools sort: can't open "temporarySam": No such file or directory<br />[bwa_aln_core] convert to sequence coordinate... 1.00 sec<br />[bwa_aln_core] refine gapped alignments... 6.07 sec<br />[bwa_aln_core] print alignments... PREPROCESS:<br />Fastq format is recognized<br />[Thu Jun 14 18:16:47 2018] Building bwa index...<br />bwa index -p all_p_ctg.fa /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa<br />[Thu Jun 14 18:18:35 2018] Finding the SA coordinates of the reads using BWA aln...<br />[Thu Jun 14 18:58:37 2018] Generate alignments of reads using bwa sampe...<br />bwa samse -n 1 all_p_ctg.fa read.sai - | grep '\(^@\|XT:A:U\)' | /usr/local/bin/samtools view -S -h -b -F 0x4 - | /usr/local/bin/samtools sort -@ 20 -no - temporarySam &gt; FALCON-Unzip-Scaff.bam<br />Mapping long-reads using blasr...<br />/home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr -nproc 40 -m 1 -minMatch 5 -bestn 10 -noSplitSubreads -advanceExactMatches 1 -nCandidates 1 -maxAnchorsPerPosition 1 -sdpTupleSize 7 /media/urbe/MyDDrive/ONTdata/allONT/allONT.fasta /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa | cut -d ' ' -f1-5,7-12 | sed 's/ /\t/g' &gt; FALCON-Unzip-Scaff.map<br />sh: 1: /home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr: Permission denied<br />Sorting mapping results...<br />sort -k1,1 -k9,9g FALCON-Unzip-Scaff.map &gt; FALCON-Unzip-Scaff.map.sort<br />Analyzing sorted results...<br />Extracting linking information...<br />i3 2000 5000<br />i2 1000 2000<br />i4 5000 15000<br />i0 -200 300<br />i5 15000 40000<br />i1 300 1000<br />Repeat detection...<br />/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl pairedEdges_i0 contig_length.dat 100 2<br />Illegal division by zero at /home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl line 93.<br />readline() on closed filehandle FILE at bin/OPERA-long-read.pl line 250.<br />rm anchor_contig_info.dat contig_length.dat filtered_edges.dat filtered_edges_cov.dat *.sai<br />rm: cannot remove 'anchor_contig_info.dat': No such file or directory<br />mv FALCON-Unzip-Scaff.bam FALCON-Unzip-Scaff-with-repeat.bam<br />/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_repeat.pl FALCON-Unzip-Scaff-with-repeat.bam repeat.dat | /usr/local/bin/samtools view - -h -S -b &gt; FALCON-Unzip-Scaff.bam<br />rm FALCON-Unzip-Scaff-with-repeat.bam<br />/home/urbe/Tools/OPERA-LG_v2.0.6/bin/OPERA-LG config &gt; log<br />Analyzing 1 library: FALCON-Unzip-Scaff.bam<br />min library mean : 0<br />minimum contig length is 500<br />Current library: 1 out of 7<br />Analyzing file: pairedEdges_no_repeat_i0<br />Analyzing file: pairedEdges_no_repeat_i1<br />Analyzing file: pairedEdges_no_repeat_i2<br />Analyzing file: pairedEdges_no_repeat_i3<br />Analyzing file: pairedEdges_no_repeat_i4<br />Analyzing file: pairedEdges_no_repeat_i5<br />ln -s results/scaffoldSeq.fasta scaffoldSeq.fasta</p><p>To resolve this, try downloading blasr version 1.3 above and re-run :)</p>]]></description>
	<dc:creator>Jit</dc:creator>
	<enclosure url="https://bioinformaticsonline.com/file/download/36945" length="0" type="inode/x-empty" />
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37396/converting-a-vcf-into-a-fasta-given-some-reference</guid>
	<pubDate>Fri, 20 Jul 2018 10:03:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37396/converting-a-vcf-into-a-fasta-given-some-reference</link>
	<title><![CDATA[Converting a VCF into a FASTA given some reference !]]></title>
	<description><![CDATA[<p>Samtools/BCFtools (Heng Li) provides a Perl script&nbsp;<a href="https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl"><code>vcfutils.pl</code></a>&nbsp;which does this, the function&nbsp;<code>vcf2fq</code>&nbsp;(lines 469-528)</p><p>This script has been modified by others to convert InDels as well, e.g.&nbsp;<a href="https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl">this</a>&nbsp;by David Eccles</p><pre><code><span>./</span><span>vcf2fq</span><span>.</span><span>pl </span><span>-</span><span>f </span><span>&lt;</span><span>input</span><span>.</span><span>fasta</span><span>&gt;</span><span> </span><span>&lt;</span><span>all</span><span>-</span><span>site</span><span>.</span><span>vcf</span><span>&gt;</span><span> </span><span>&gt;</span><span> </span><span>&lt;</span><span>output</span><span>.</span><span>fastq</span><span>&gt;</span></code></pre><p>https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl</p><p>https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</guid>
	<pubDate>Thu, 14 May 2020 15:09:52 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41673/lr-gapcloser-a-tiling-path-based-gap-closer-that-uses-long-reads-to-complete-genome-assembly</link>
	<title><![CDATA[LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly]]></title>
	<description><![CDATA[<p>LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.</p><p>Address of the bookmark: <a href="https://github.com/CAFS-bioinformatics/LR_Gapcloser" rel="nofollow">https://github.com/CAFS-bioinformatics/LR_Gapcloser</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38006/scribl-html5-canvas-genomics-graphic-library</guid>
	<pubDate>Thu, 25 Oct 2018 09:38:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38006/scribl-html5-canvas-genomics-graphic-library</link>
	<title><![CDATA[Scribl : HTML5 canvas genomics graphic library]]></title>
	<description><![CDATA[<p>Scribl is a javascript, Canvas-based graphics library that easily generates biological visuals of genomic regions, alignments, and assembly data. Scribl can also be used in conventional offline pipelines, since everything needed to generate charts can be contained in a single html file.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://chmille4.github.io/Scribl/" rel="nofollow">http://chmille4.github.io/Scribl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>