<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/30336?offset=100 https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial Fri, 09 Dec 2016 04:19:07 -0600 https://bioinformaticsonline.com/bookmarks/view/30093/velvet-tutorial <![CDATA[Velvet tutorial]]> The objective of this activity is to help you understand how to run Velvet in general, how to accurately estimate the insert size of a paired-end library through the use of Bowtie, the primary parameters of velvet, and the process involved in producing a de novo assembly from Illumina reads.

http://evomics.org/learning/assembly-and-alignment/velvet/

Address of the bookmark: http://evomics.org/learning/assembly-and-alignment/velvet/

]]> Poonam Mahapatra https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite Fri, 23 Dec 2016 08:49:55 -0600 https://bioinformaticsonline.com/bookmarks/view/30355/meme-suite <![CDATA[MEME suite]]> Motif based sequence analysis suits 

The MEME Suite allows the biologist to discover novel motifs in collections of unaligned nucleotide or protein sequences, and to perform a wide variety of other motif-based analyses.

The MEME Suite supports motif-based analysis of DNA, RNA and protein sequences. It provides motif discovery algorithms using both probabilistic (MEME) and discrete models (MEME), which have complementary strengths. It also allows discovery of motifs with arbitrary insertions and deletions (GLAM2). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (FIMO, MAST and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between motifs (SpaMo), predicting the biological roles of motifs (GOMo), measuring the positional enrichment of sequences for known motifs (CentriMo), and analyzing ChIP-seq and other large datasets (MEME-ChIP).

The MEME Suite is comprised of a collection of tools that work together, as shown below. Not all the tools are available as webservices, so to get the full power of the MEME Suite you will need to download and install a local copy of the software. To see what has changed recently you can peruse the release notes.

http://meme-suite.org/

Address of the bookmark: http://meme-suite.org/

]]> Bulbul https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter Mon, 13 Feb 2017 08:40:23 -0600 https://bioinformaticsonline.com/bookmarks/view/30897/finestructure-v2-globetrotter <![CDATA[fineSTRUCTURE v2 & GLOBETROTTER]]> Software available at this site

  • FineSTRUCTURE version 2, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the Downloads page.
  • FineSTRUCTURE R scripts, a facility for exploring the results when the GUI is unavailable.
  • GLOBETROTTER, the admixture dating method based on ChromoPainter. Download from the Downloads page.
  • AdmixturePainting, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.
  • RADpainter, finestructure and ChromoPainter for RAD tag data used for non-model organisms.
  • Scripts to perform many types of conversion. Included in the main software download from the Downloads page.
What this page is This page provides information about and downloads for methodology for Chromosome Painting. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!
About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.

Address of the bookmark: http://paintmychromosomes.com/

]]> Shruti Paniwala https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes Sun, 02 Apr 2017 15:53:47 -0500 https://bioinformaticsonline.com/bookmarks/view/32018/tmap-torrent-mapping-alignment-program-general-notes <![CDATA[TMAP - torrent mapping alignment program General Notes]]> TMAP - torrent mapping alignment program General Notes

TMAP is a fast and accurate alignment software for short and long nucleotide sequences produced by next-generation sequencing technologies.

  • The latest TMAP is unsupported. To use a supported version, please see the TMAP version associated with a Torrent Suite release below.

  • Get the latest source code:

    git clone git://github.com/iontorrent/TMAP.git
 cd TMAP
 git submodule init
 git submodule update

https://github.com/iontorrent/TS/tree/master/Analysis/TMAP

Address of the bookmark: https://github.com/iontorrent/TS/tree/master/Analysis/TMAP

]]> Poonam Mahapatra https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2 Mon, 10 Apr 2017 04:45:40 -0500 https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2 <![CDATA[WGS Celera Assembler version 8.3rc2]]> These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.

This distribution package provides a stable, tested, documented version of the software.  The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.

The source code package includes full source code (revision 4627), Makefiles, and scripts.  A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.  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].

Full documentation can be found online at http://wgs-assembler.sourceforge.net/.

Interesting scripts within it

urbe@urbo214b[bin] ls                                                        []
-rwxrwxr-x 1 urbe urbe  11K Apr 10 11:41 addCNSToStore
-rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs
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-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds
-rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta
-rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics
-rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl
-rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr
-rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart
-rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus
-rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness
-rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap
-rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs
-rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs
-rwxrwxr-x 1 urbe urbe  18K Apr 10 11:41 ca2ace.pl
-rwxrwxr-x 1 urbe urbe  12K Apr 10 11:41 caqc_help.ini
-rwxrwxr-x 1 urbe urbe  61K Apr 10 11:41 caqc.pl
-rwxrwxr-x 1 urbe urbe  23K Apr 10 11:41 cat-corrects
-rwxrwxr-x 1 urbe urbe  24K Apr 10 11:41 cat-erates
-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw
-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump
-rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe
-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera
-rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates
-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply
-rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise
-rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat
-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl
-rwxrwxr-x 1 urbe urbe  48K Apr 10 11:41 convertOverlap
-rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA
-rwxrwxr-x 1 urbe urbe  20K Apr 10 11:41 convertToPBCNS
-rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags
-rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps
-rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio
-rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns
-rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate
-rwxrwxr-x 1 urbe urbe  37K Apr 10 11:41 demotePosMap
-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles
-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore
-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons
-rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate
-rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold
-rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges
-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition
-rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages
-rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense
-rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA
-rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze
-rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample
-rwxrwxr-x 1 urbe urbe  62K Apr 10 11:40 fastqSimulate
-rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort
-rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA
-rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap
-rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim
-rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs
-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth
-rwxrwxr-x 1 urbe urbe  29K Apr 10 11:41 fragsInVars
-rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones
-rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper
-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench
-rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate
-rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ
-rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling
-rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM
-rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim
-rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish
-rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique
-rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique
-rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy
-rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl
-rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim
-rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply
-rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl
-rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses
-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds
-rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout
-rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore
-rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition
-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats
-rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore
-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer
-rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild
-rwxrwxr-x 1 urbe urbe  33K Apr 10 11:41 overlapStoreIndexer
-rwxrwxr-x 1 urbe urbe  48K Apr 10 11:41 overlapStoreSorter
-rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry
lrwxrwxrwx 1 urbe urbe    4 Apr 10 11:41 pacBioToCA -> PBcR
-rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR
-rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon
-rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns
-rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment
-rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap
-rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq
-rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap
-rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates
-rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache
-rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA
-rwxrwxr-x 1 urbe urbe  88K Apr 10 11:41 runCA-dedupe
-rwxrwxr-x 1 urbe urbe  14K Apr 10 11:41 runCA-overlapStoreBuild
-rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh
-rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA
-rwxrwxr-x 1 urbe urbe  13K Apr 10 11:40 show-corrects
-rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs
-rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator
drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR
-rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore
-rwxrwxr-x 1 urbe urbe  35K Apr 10 11:41 tracearchiveToCA
-rwxrwxr-x 1 urbe urbe  35K Apr 10 11:41 tracedb-to-frg.pl
-rwxrwxr-x 1 urbe urbe  44K Apr 10 11:41 trimFastqByQVWindow
-rwxrwxr-x 1 urbe urbe  18K Apr 10 11:40 uidclient
-rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger
-rwxrwxr-x 1 urbe urbe  42K Apr 10 11:40 upgrade-v8-to-v9
-rwxrwxr-x 1 urbe urbe  42K Apr 10 11:40 upgrade-v9-to-v10
-rwxrwxr-x 1 urbe urbe  854 Apr 10 11:41 utg2fasta
-rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns
-rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix


Address of the bookmark: http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page

]]> Jit https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop Tue, 18 Apr 2017 04:28:19 -0500 https://bioinformaticsonline.com/bookmarks/view/32184/metagenomics-assembly-workshop <![CDATA[Metagenomics assembly workshop !!]]>
Next 

 

Address of the bookmark: http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html

]]> Jit https://bioinformaticsonline.com/opportunity/view/43272/bioinformatics-head-bioinformatics-manager-iii-cancer-genomics-research-laboratory-at-frederick-national-laboratory Wed, 18 Aug 2021 00:19:48 -0500 <![CDATA[Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at Frederick National Laboratory]]> Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR). CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

]]> https://bioinformaticsonline.com/researchlabs/view/5209/anders-krogh-lab Mon, 30 Sep 2013 19:07:40 -0500 <![CDATA[Anders Krogh Lab]]> In a lot of my work in bioinformatics, I have been using hidden Markov models (HMMs). As a postdoc with David Haussler at UCSC we developed the so-called profile HMMs (refs). Since then I have applied HMMs to membrane proteins (refs) and gene identification (refs) and have worked on methods for such things as discriminative estimation of HMMs (refs) and alternative decoding algorithms etc. (refs).

Now my main interests are in gene regulation, where we work on promoter analysis; non-coding RNA, where miRNAs and structure prediction are the main areas; and protein structure, where the group is working on methods for structure prediction from sequence. To read more about these topics, please see the research pages.

Lab page @ http://wiki.binf.ku.dk/User:Krogh

]]> https://bioinformaticsonline.com/opportunity/view/4946/crcri-bioinfomatics-walk-in-on-08102013 Fri, 27 Sep 2013 10:59:53 -0500 <![CDATA[CRCRI Bioinfomatics Walk In on 08.10.2013]]> Walk-in-Interview for recruitment of one Project Fellow for a period of 10 months purely on temporary basis is proposed to be held at Central Tuber Crops Research Institute, Sreekariyam, Thiruvananthapuram for a KSCSTE funded project entitled “PARTICIPATORY DEVELOPMENT OF A WEB BASED USER FRIENDLY CASSAVA EXPERT SYSTEM”

Salary: Rs. 10,000/- per month.

Age limit: 35 for men and 40 for women & SC/ST.

Qualification: First class in M. Sc (Agriculture)/MCA/M.Sc (IT)/ M. Sc (Computer Application)/M.Sc (Bioinformatics)/M.Sc (Geoinformatics).

Desirable: Two years experience in web design and web programming.

Date & time of interview: 08.10.2013, 10 am

Interested candidates may appear for an interview at this institute along with their application in plain paper containing the following particulars viz. (1) Name (2) Father/Husband/Guardian’s Name (3) date of birth & age as on 01.10.2013 (4) Permanent address (5) Address for communication (6) Email address and Telephone No. with code (7) Qualification (8) National fellowship like ICAR/CSIR/UGC etc. if any (9) Whether SC/ST/OBC (10) Details of experience (Attested copies of degree certificate, proof of age, mark sheets). Original certificates should be produced for verification.

No TA/DA will be admissible to the candidates attending the test. The selected candidate will have to join immediately.

Advertisement: http://www.ctcri.org/careers/mithra_SRF.doc

]]> https://bioinformaticsonline.com/researchlabs/view/44226/rotifers-lab Wed, 08 Mar 2023 23:23:14 -0600 <![CDATA[Rotifers Lab]]> For scientists in the MBL’s Gribble Lab, the rotifer (Brachionus manjavacas) is used as a model organism to study evolution, stress responses, the biology of aging, and maternal effects. Rotifers are small, easy to grow in the lab, have a short lifespan, and share many of their genes with humans. That makes them ideal specimens in which to address questions relevant to human health as well as understand basic biological and evolutionary processes. Brachionus rotifers produces eggs that can be completely dried and frozen for decades, then hatch within a day when exposed to water and light.

https://www.mbl.edu/research/research-organisms/rotifer
https://gribblebiolab.org/

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