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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/44472?offset=150</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30976/brig</guid>
	<pubDate>Thu, 16 Feb 2017 13:14:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30976/brig</link>
	<title><![CDATA[BRIG]]></title>
	<description><![CDATA[<p>BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:<a href="http://sourceforge.net/projects/brig">http://sourceforge.net/projects/brig</a></p>
<p>If you have any questions or comments, post them on&nbsp;<a href="http://sourceforge.net/tracker/?group_id=328245">one of the trackers</a>&nbsp;on BRIG&rsquo;s SourceForge page:<a href="http://sourceforge.net/tracker/?group_id=328245">http://sourceforge.net/tracker/?group_id=328245</a>.</p>
<p>Features:</p>
<ul>
<li>Images show similarity between a central reference sequence and other sequences as concentric rings.</li>
<li>BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.</li>
<li>Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.</li>
<li>Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.</li>
<li>BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously</li>
</ul>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://brig.sourceforge.net/" rel="nofollow">http://brig.sourceforge.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</guid>
	<pubDate>Mon, 27 Feb 2017 09:54:47 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31139/pbsuite-software-for-long-read-sequencing-data-from-pacbio</link>
	<title><![CDATA[PBSuite: Software for Long-Read Sequencing Data from PacBio]]></title>
	<description><![CDATA[<p><span>PBJelly - the genome upgrading tool.&nbsp;</span><br><span>PBHoney - the structural variation discovery tool&nbsp;</span><br><br><span>Both are contained within the PBSuite code found in downloads.</span><br><br><span>----- PBJelly -----</span><br><span>Read The Paper&nbsp;</span><br><a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768" target="_blank">http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768</a><br><br><span>PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.&nbsp;</span><br><br><span>----- PBHoney -----</span><br><span>Read The Paper</span><br><a href="http://www.biomedcentral.com/1471-2105/15/180/abstract" target="_blank">http://www.biomedcentral.com/1471-2105/15/180/abstract</a><br><br><span>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.</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/pb-jelly/" rel="nofollow">https://sourceforge.net/projects/pb-jelly/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</guid>
	<pubDate>Fri, 03 Mar 2017 10:14:18 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31302/multi-metagenome-assembly</link>
	<title><![CDATA[Multi-metagenome assembly]]></title>
	<description><![CDATA[<p>This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:</p>
<p>Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes<br><br>Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, K&aring;re L. Nielsen and Per .H. Nielsen</p>
<p>Nature Biotechnology 2013, doi:&nbsp;<a href="http://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.2579.html">10.1038/nbt.2579</a></p><p>Address of the bookmark: <a href="https://github.com/MadsAlbertsen/multi-metagenome" rel="nofollow">https://github.com/MadsAlbertsen/multi-metagenome</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</guid>
	<pubDate>Fri, 10 Mar 2017 08:51:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31526/sequenceserver</link>
	<title><![CDATA[sequenceserver]]></title>
	<description><![CDATA[<p><span>SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.</span></p>
<p><span><span>More at&nbsp;</span><a href="http://sequenceserver.com/">http://sequenceserver.com</a><span>.</span></span></p><p>Address of the bookmark: <a href="https://github.com/wurmlab/sequenceserver" rel="nofollow">https://github.com/wurmlab/sequenceserver</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</guid>
	<pubDate>Fri, 05 May 2017 06:11:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32485/bacterial-genome-assembly</link>
	<title><![CDATA[Bacterial genome assembly !!]]></title>
	<description><![CDATA[<p>This tutorial will serve as an example of how to use free and open-source genome assembly and secondary scaffolding tools to generate high quality assemblies of&nbsp;bacterial sequence data. The bacterial sample used in this tutorial will be referred&nbsp;to simply&nbsp;as &ldquo;Species&rdquo; since it is&nbsp;live data. This data is paired-end data, meaning that there are forward and reverse reads, which we will designate as Sample_R1.fastq and Sample_R2.fastq, respectively.</p>
<p>https://github.com/jennomics/WorkflowPaper/blob/master/Genome%20Assembly%20and%20Annotation.md</p><p>Address of the bookmark: <a href="http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/" rel="nofollow">http://bioinformatics.uconn.edu/bacterial-genome-assembly-tutorial/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</guid>
	<pubDate>Tue, 03 Jul 2018 08:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37233/rna-seq-analysis-workshop-course-materials</link>
	<title><![CDATA[RNA-seq Analysis Workshop Course Materials]]></title>
	<description><![CDATA[RNAseq can be roughly divided into two "types":

Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw);

Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well.
In this lesson we will focus on the Reference genome-based type of RNA seq.

http://chagall.med.cornell.edu/RNASEQcourse/<p>Address of the bookmark: <a href="http://chagall.med.cornell.edu/RNASEQcourse/" rel="nofollow">http://chagall.med.cornell.edu/RNASEQcourse/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35983/some-useful-bioinformatics-links</guid>
	<pubDate>Fri, 16 Mar 2018 20:50:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35983/some-useful-bioinformatics-links</link>
	<title><![CDATA[Some useful Bioinformatics links]]></title>
	<description><![CDATA[<p><br /> Reference-free prediction of rearrangement breakpoint reads | Bioinformatics | Oxford Academic</p><p>https://academic.oup.com/bioinformatics/article/30/18/2559/2475628<br /> Reference-free SNP detection: dealing with the data deluge</p><p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083407/<br /> GATB/DiscoSnp: DiscoSnp is designed for discovering all kinds of SNPs (not only isolated ones), as well as insertions and deletions, from raw set(s) of reads.</p><p>https://github.com/GATB/DiscoSnp<br /> De novo assembly | Oxford Nanopore Technologies</p><p>https://nanoporetech.com/taxonomy/term/131<br /> De novo long-read assembly of a complex animal genome | bioRxiv</p><p>https://www.biorxiv.org/content/early/2017/09/10/187054<br /> Rapid de novo assembly of the European eel genome from nanopore sequencing reads | Scientific Reports</p><p>https://www.nature.com/articles/s41598-017-07650-6.epdf?author_access_token=dktG7e98wyRJnaEEMTcPqtRgN0jAjWel9jnR3ZoTv0P7E7t-wVGo30iojNO7dICajNY_7PE5xVPv6OoLe7hn9TeUjcZ5umREOzNoPMWkfYH58RS6uxm3vm4e4BG2AA_WKW84i6egKK271NwMq-NfzA%3D%3D<br /> nanoporetech/ont-assembly-polish: ONT assembly and Illumina polishing pipeline</p><p>https://github.com/nanoporetech/ont-assembly-polish<br /> Generade-nl/TULIP: TULIP - The Uncorrected Long read Itegration Pipeline</p><p>https://github.com/Generade-nl/TULIP<br /> www.nature.com</p><p>https://www.nature.com/articles/s41598-017-03996-z<br /> Example gallery of NanoPlot &ndash; Gigabase or gigabyte</p><p>https://gigabaseorgigabyte.wordpress.com/2017/06/01/example-gallery-of-nanoplot/<br /> Tool documentation</p><p>https://broadinstitute.github.io/picard/command-line-overview.html<br /> Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. - PubMed - NCBI</p><p>https://www.ncbi.nlm.nih.gov/pubmed/24185095<br /> MAFFT ver.7 - a multiple sequence alignment program</p><p>https://mafft.cbrc.jp/alignment/software/algorithms/algorithms.html<br /> Measuring the distance between multiple sequence alignments | Bioinformatics | Oxford Academic</p><p>https://academic.oup.com/bioinformatics/article/28/4/495/212883<br /> The MUMmer 3 examples</p><p>http://mummer.sourceforge.net/examples/<br /> MAFFT ver.7 - a multiple sequence alignment program</p><p>https://mafft.cbrc.jp/alignment/software/tips.html<br /> Omega | Overlap-graph de novo Assembler for Metagenomics</p><p>https://omega.omicsbio.org/<br /> abiswas-odu/Disco: Multi-threaded Distributed Memory Overlap-Layout-Consensus (OLC) Metagenome Assembler</p><p>https://github.com/abiswas-odu/Disco<br /> SAGE: String-overlap Assembly of GEnomes | BMC Bioinformatics | Full Text</p><p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-302</p><p>Fast and sensitive mapping of nanopore sequencing reads with GraphMap | Nature Communications</p><p>https://www.nature.com/articles/ncomms11307<br /> lumpy-sv/extractSplitReads_BwaMem at master &middot; arq5x/lumpy-sv</p><p>https://github.com/arq5x/lumpy-sv/blob/master/scripts/extractSplitReads_BwaMem<br /> jts/nanocorrect: Experimental pipeline for correcting nanopore reads</p><p>https://github.com/jts/nanocorrect</p><p>video - how to install flash plugin on ubuntu 14.04 LTS 64-bit version - Ask Ubuntu</p><p>https://askubuntu.com/questions/469553/how-to-install-flash-plugin-on-ubuntu-14-04-lts-64-bit-version<br /> lh3/fermi: A WGS de novo assembler based on the FMD-index for large genomes</p><p>https://github.com/lh3/fermi<br /> Multi-metagenome</p><p>http://madsalbertsen.github.io/multi-metagenome/docs/step9.html<br /> Bandage by rrwick</p><p>https://rrwick.github.io/Bandage/<br /> Codon Optimization OnLine (COOL): a web-based multi-objective optimization platform for synthetic gene design | Bioinformatics | Oxford Academic</p><p>https://academic.oup.com/bioinformatics/article/30/15/2210/2391162<br /> Genome Architecture and Evolution of a Unichromosomal Asexual Nematode - ScienceDirect</p><p>https://www.sciencedirect.com/science/article/pii/S096098221731076X?via%3Dihub#fig4<br /> How to determine chimeras in my de novo assembly? - SEQanswers</p><p>http://seqanswers.com/forums/showthread.php?t=26721<br /> samtools(1) manual page</p><p>http://www.htslib.org/doc/samtools.html<br /> How To Filter Mapped Reads With Samtools</p><p>https://www.biostars.org/p/56246/<br /> The MUMmer 3 manual</p><p>http://mummer.sourceforge.net/manual/#nucmer<br /> assembly_olc.pdf</p><p>http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_olc.pdf<br /> SAM and BAM filtering oneliners</p><p>https://gist.github.com/davfre/8596159<br /> Inroduction to dot-plots</p><p>http://www.code10.info/index.php%3Foption%3Dcom_content%26view%3Darticle%26id%3D64:inroduction-to-dot-plots%26catid%3D52:cat_coding_algorithms_dot-plots%26Itemid%3D76<br /> RepeatFinder Home Page</p><p>http://www.cbcb.umd.edu/software/RepeatFinder/<br /> RepeatFinderReprint.pdf</p><p>http://www.cbcb.umd.edu/software/RepeatFinder/RepeatFinderReprint.pdf<br /> https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html</p><p>https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html<br /> Circular Visualization in R</p><p>http://zuguang.de/circlize_book/book/introduction.html#a-qiuck-glance<br /> Creating a coverage plot using BEDTools and R</p><p>https://davetang.org/muse/2015/08/05/creating-a-coverage-plot-using-bedtools-and-r/<br /> Eval: A software package for analysis of genome annotations | BMC Bioinformatics | Full Text</p><p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-4-50<br /> eval-documentation.pdf</p><p>http://mblab.wustl.edu/media/software/eval-documentation.pdf<br /> OmicCircos: A Simple-to-Use R Package for the Circular Visualization of Multidimensional Omics Data</p><p>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3921174/<br /> sequence - download.tardigrades.org &gt; v1 &gt; sequence</p><p>http://download.tardigrades.org/v1/sequence/<br /> ksahlin/BESST: BESST - scaffolder for genomic assemblies</p><p>https://github.com/ksahlin/BESST<br /> reubwn/scripts: Useful scripts for various things</p><p>https://github.com/reubwn/scripts<br /> ICEberg</p><p>http://db-mml.sjtu.edu.cn/ICEberg/index.php<br /> Satsuma - Evolution and Genomics</p><p>http://evomics.org/learning/genomics/satsuma/<br /> A complete bacterial genome assembled de novo using only nanopore sequencing data | Nature Methods</p><p>https://www.nature.com/articles/nmeth.3444<br /> vezzi/FRC_align: Computes FRC from SAM/BAM file and not from afg files</p><p>https://mail.google.com/mail/u/0/#inbox<br /> Read GTF file into R - Dave Tang's blog</p><p>https://davetang.org/muse/2017/08/04/read-gtf-file-r/</p><p>https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html</p><p>https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html<br /> Dot: Interactive dot plot for genome-genome alignments</p><p>https://dnanexus.github.io/dot/<br /> Zoho Accounts</p><p>https://accounts.zoho.eu/signin?servicename=ZohoProjects&amp;serviceurl=https%3A%2F%2Fprojects.zoho.eu%2Fportal%2Favaga2<br /> lh3/minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences</p><p>https://github.com/lh3/minimap2<br /> SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information | BMC Bioinformatics | Full Text</p><p>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-211<br /> Palindromic gene amplification &mdash; an evolutionarily conserved role for DNA inverted repeats in the genome | Nature Reviews Cancer</p><p>https://www.nature.com/articles/nrc2591<br /> bioinformatics - BLAST DNA Sequences Reversed - Biology Stack Exchange</p><p>https://biology.stackexchange.com/questions/8160/blast-dna-sequences-reversed<br /> LASTZ</p><p>http://www.bx.psu.edu/miller_lab/dist/README.lastz-1.02.00/README.lastz-1.02.00a.html<br /> SOGo - (1652) Inbox</p><p>https://sogo.unamur.be/SOGo/so/jnarayan/Mail/view<br /> Tetra-Nucleotide Analysis (TNA) | BIOiPLUG Help center</p><p>http://help.bioiplug.com/tetra-nucleotide-analysis-tna/</p><p>Clustering metagenomic contigs on tetranucleotide frequency &mdash; CGAT documentation</p><p>http://cgat.readthedocs.io/en/latest/recipes/metagenome_contigs_kmers.html</p><p>&nbsp;</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</guid>
	<pubDate>Fri, 07 Dec 2018 08:04:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38378/gwaspro-a-high-performance-genome-wide-association-analysis-server</link>
	<title><![CDATA[GWASpro: A High-Performance Genome-Wide Association Analysis Server]]></title>
	<description><![CDATA[<p>GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://bioinfo.noble.org/GWASPRO/" rel="nofollow">https://bioinfo.noble.org/GWASPRO/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>

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