BOL: Related items

Bioinformatics WalkIn at NII

Fri, 04 Sep 2015 21:48:15 -0500

ADVERTISEMENT OF WALK-IN-INTERVIEW

NAME OF THE POST : Bioinformatician (Part time 3 days in a week) (One Position only)

DURATION : One Year

NAME OF THE PROJECT : Next generation sequencing facility

EDUCATIONAL QUALIFICATIONS : At least a Masters degree in Bioinformatics and Bachelors degree in any stream of life sciences

REQUIREMENTS :

Around 5 years of experience and proven track record in next generation sequence data analysis (supported by publications in peer-reviewed journals), ability to analyze transcriptomics, Chip-seq, and small RNA –seq data.

: Should have the ability to analyze raw primary data generated by Illumina next generation sequencing platforms and create / troubleshoot custom analysis Pipelines.

Should have ability to handle all downstream secondary and tertiary data analysis using commercially available as well as open source softwares (transcriptomics, ChIP-seq, small RNA-seq)

Apart from these, the applicant should have knowledge of the following: Programming: Perl and Python. Operating system:

Linux and Windows. NGS Analysis tools: Maq, BWA, Bowtie, SAM tools, BEDTools, MACS, Galaxy, FastQC, Bismark, MEDIPS, Tophat, Cufflinks, AvadisNGS, CLC Genomics Workbench, Galaxy, BaseSpace, Trinity Statistics: Microsoft Excel and R. Database: MySQL Genome Browser: UCSC, Ensemble, IGV, IGB Motif Analysis Tools: MEME Suite, Transfac and RSAT Functional Annotation Tools: DAVID, GeneCodis, Gene Cards Networking Tools: Cytoscape

EMOLUMENTS : The incumbent will be paid a fee of Rs. 2000/- per sitting/ per day.

SCIENTIST NAME : Dr. Arnab Mukhopadhyay,

Staff Scientific V Next generation sequencing facility

SCIENTIST’S E-MAIL ID : arnab@nii.ac.in

WALK IN INTERVIEW ON : 18th September, 2015

REGISTRATION OF CANDIDATES: 10.30 AM to 11.00 AM

PLEASE NOTE- 1. CANDIDATE MAY FILL UP APPLICATION IN THE PRECRIBED FORMAT ALONG WITH NECESSARY DOCUMENTS FOR VERIFICATION. 2. APPLICATIONS CONTAINING INCOMPLETE INFORMATION SHALL NOT BE ENTERTAINED. 3. DATE OF PASSING THE EXAMINATIONS MUST BE INDICATED CLEARLY. 4. ONLY REGISTERED CANDIDATES WILL BE INTERVIEWED. 5. NO TA/DA WILL BE PAID FOR ATTENDING THE INTERVIEW PRESCRIBED FORM 1. NAME 2. FATHER’S NAME 3. MOTHER’S NAME 4. DATE OF BIRTH 5. SEX (MALE/FEMALE) 6. CATEGORY (SC/ ST/ OBC/ PH) 7. ADDRESS a. (CORRSPONDENCE) b. (PERMANENT) 8. E MAIL, TELEPHONE NO. & MOBILE No (if any) 9. ACADEMIC & PROFESSIONAL QUALIFICATIONS NAME OF EXAMINATION PASSED WITH SUBJECTS YEAR OF PASSING BOARD/ UNIVERSITY PERCENTAGE/ DIVISION REMARKS 10. PAST EXPERIENCE & PRESENT EMPLOYMENT, IF ANY 11. CANDIDATES SHOULD STATE CLEARLY WHETHER THEY HAVE BEEN AWARDED PH.D DEGREE OR THESIS HAS BEEN SUBMITTED. 12. HAVE YOU APPLIED FOR A POSITION EARLIER IN THE INSTITUTE? IF SO:- (1) THE DETAILS OF THE PROJECT AND PROJECT INVESTIGATOR (2) IF CALLED FOR INVERVIEW, RESULTS THEREOF

More at http://www1.nii.res.in/sites/default/files/walkininterview-18sept2015.pdf

BioinfoLab

Fri, 25 Mar 2016 11:05:35 -0500

Laboratory of Statistics and Computational tools for Bioinformatics

The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The laboratory has been officially opened in 2012 with the support of Programma Operativo Nazionale "Ricerca e Competitività" 2007-2013 (PON "R&C"), and it incorporates several expertise and research activities started since 2007, and supported by several CNR projects. Main interest of BioinfoLab is to develop novel statistical methods and computational tools for the analysis of high dimensional data arising from "Multi-omics" applications. In particular, current activities involve the analysis of ChIP-seq and RNA-seq experiments.

More at http://bioinfo.na.iac.cnr.it/BioinfoLab/index.html

Stand-alone programs for Bioinformatician

Radha Agarkar — Sat, 21 May 2016 22:50:15 -0500

This directory contains applications for stand-alone use, built specifically for a Linux 64-bit machine.

For help on the bigBed and bigWig applications see:
http://genome.ucsc.edu/goldenPath/help/bigBed.html
http://genome.ucsc.edu/goldenPath/help/bigWig.html

View the file 'FOOTER' to see the usage statement for each of the applications.

Address of the bookmark: http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/

Finding Patterns in Biological Sequences

Jit — Thu, 22 Dec 2016 10:30:49 -0600

In this report we provide an overview of known techniques for discovery of patterns of biological sequences (DNA and proteins). We also provide biological motivation, and methods of biological verification of such patterns. Finally we list publicly available tools and databases for pattern discovery. On-line supplement is available through http://genetics.uwaterloo.ca/∼tvinar/cs798g/motif.

Address of the bookmark: http://engr.case.edu/li_jing/papers/00798gpattern.pdf

WGS Celera Assembler version 8.3rc2

Jit — Mon, 10 Apr 2017 04:45:40 -0500

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
-rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest
-rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap
-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
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-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
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-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
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-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
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-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
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-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

Binding Site Prediction in Protein !

Poonam Mahapatra — Wed, 25 Apr 2018 04:35:57 -0500

The interaction between proteins and other molecules is fundamental to all biological functions. In this section we include tools that can assist in prediction of interaction sites on protein surface and tools for predicting the structure of the intermolecular complex formed between two or more molecules (docking).

Pockets Identification

CASTp

Automatic Identification of pockets and cavities in proteins structure, and quantitation of their volumes using Delaunay triangulation. Available also as PyMOL plugin

Pocket-Finder

Automatic identification of pockets and cavities in proteins structure, and quantitation of their volumes.

PocketPicker

Grid-based technique for the analysis of protein pockets. PocketPicker available as a plugin for PyMOL

Binding Site Prediction

ConSurf

Identification of functional regions in proteins by surface-mapping of phylogenetic information

CRESCENDO

Identification protein interaction sites. It uses sequence conservation patterns in homologous proteins to distinguish between residues that are conserved due to structural restraints from those due to functional restraints.

Ligand Binding Sites

3DLigandSite

The server utilizes protein-structure prediction to provide structural models of the binding site. Ligands bound to structures are superimposed onto the model and use to predict the binding site.

FINDSITE

A threading-based method for ligand-binding site prediction and functional annotation based on binding-site similarity across superimposed groups of threading templates.

LIGSITE^csc

Prediction of binding site by pocket identification using the Connolly surface and degree of conservation

metaPocketA meta server for ligand-binding site prediction. metaPocket use LIGSITE^csc, PASS, Q-SiteFinder and SURFNET

Installing python-numpy !

Jit — Mon, 07 May 2018 04:31:25 -0500

$ sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
[sudo] password for urbe:
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following packages were automatically installed and are no longer required:
bridge-utils containerd linux-headers-4.4.0-116 linux-headers-4.4.0-116-generic linux-headers-4.4.0-21 linux-headers-4.4.0-21-generic
linux-image-4.4.0-116-generic linux-image-4.4.0-21-generic linux-image-extra-4.4.0-116-generic linux-image-extra-4.4.0-21-generic
linux-signed-image-4.4.0-116-generic runc ubuntu-fan
Use 'sudo apt autoremove' to remove them.
The following additional packages will be installed:
blt fonts-lyx fonts-mathjax ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2 libhdf5-10 libjs-highlight
libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4 python-chardet python-cvxopt
python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging python-jdcal python-jinja2 python-joblib
python-lxml python-markupsafe python-matplotlib-data python-mpmath python-numexpr python-openpyxl python-pandas-lib python-patsy python-pexpect
python-pil python-ptyprocess python-py python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-simplegeneric
python-simplejson python-statsmodels python-statsmodels-lib python-sympy-doc python-tables python-tables-data python-tables-lib python-tk
python-tornado python-tz python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera
Suggested packages:
blt-demo ipython-doc ipython-qtconsole python-pygments nodejs pandoc libiodbc2-dev libmysqlclient-dev gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info
| gsl-ref-html libjs-jquery-ui-docs fonts-mathjax-extras libjs-mathjax-doc python-gtk2-doc python-genshi python-jinja2-doc python-lxml-dbg
python-lxml-doc ffmpeg inkscape python-cairocffi python-configobj python-excelerator python-matplotlib-doc python-qt4 python-sip python-traits
python-wxgtk3.0 ttf-staypuft python-gmpy2 python-mpmath-doc python-coverage python-nose-doc python-numpy-dbg python-numpy-doc python-pandas-doc
python-patsy-doc python-pexpect-doc python-pil-doc python-pil-dbg subversion python-pytest-xdist libcurl4-gnutls-dev python-pycurl-dbg
python-pycurl-doc python-pymysql-doc python-mock python-scipy-doc python-statsmodels-doc python-tables-doc python-netcdf vitables tix
python-tk-dbg
The following NEW packages will be installed:
blt fonts-lyx fonts-mathjax ipython ipython-notebook ipython-notebook-common isympy libaec0 libamd2.4.1 libdsdp-5.8gf libglpk36 libgsl2
libhdf5-10 libjs-highlight libjs-highlight.js libjs-jquery-ui libjs-marked libjs-mathjax libjs-underscore libsz2 python-antlr python-bs4
python-chardet python-cvxopt python-cycler python-dateutil python-decorator python-glade2 python-gmpy python-html5lib python-imaging
python-jdcal python-jinja2 python-joblib python-lxml python-markupsafe python-matplotlib python-matplotlib-data python-mpmath python-nose
python-numexpr python-numpy python-openpyxl python-pandas python-pandas-lib python-patsy python-pexpect python-pil python-ptyprocess python-py
python-pycurl python-pyglet python-pymysql python-pyparsing python-pytest python-scipy python-simplegeneric python-simplejson python-statsmodels
python-statsmodels-lib python-sympy python-sympy-doc python-tables python-tables-data python-tables-lib python-tk python-tornado python-tz
python-xlrd python-xlwt python-zmq tk8.6-blt2.5 ttf-bitstream-vera
0 upgraded, 73 newly installed, 0 to remove and 35 not upgraded.
Need to get 49,5 MB of archives.
After this operation, 271 MB of additional disk space will be used.
Do you want to continue? [Y/n] Y
Get:1 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-pymysql all 0.7.2-1ubuntu1 [56,4 kB]
Get:2 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 tk8.6-blt2.5 amd64 2.5.3+dfsg-3 [574 kB]
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Get:18 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-markupsafe amd64 0.23-2build2 [15,5 kB]
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Get:20 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-pycurl amd64 7.43.0-1ubuntu1 [43,3 kB]
Get:21 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tornado amd64 4.2.1-1ubuntu3 [273 kB]
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Get:33 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-chardet all 2.3.0-2 [96,3 kB]
Get:34 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 libdsdp-5.8gf amd64 5.8-9.1ubuntu2 [192 kB]
Get:35 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-cvxopt amd64 1.1.4-1.4 [1.344 kB]
Get:36 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-cycler all 0.9.0-1 [5.426 B]
Get:37 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-dateutil all 2.4.2-1 [42,5 kB]
Get:38 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-glade2 amd64 2.24.0-4ubuntu1 [9.078 B]
Get:39 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-gmpy amd64 1.17-1 [91,1 kB]
Get:40 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-html5lib all 0.999-4 [83,1 kB]
Get:41 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-pil amd64 3.1.2-0ubuntu1.1 [312 kB]
Get:42 http://be.archive.ubuntu.com/ubuntu xenial-updates/universe amd64 python-imaging all 3.1.2-0ubuntu1.1 [4.596 B]
Get:43 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-jdcal all 1.0-1build1 [7.702 B]
Get:44 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-joblib all 0.9.4-1 [74,6 kB]
Get:45 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-lxml amd64 3.5.0-1build1 [819 kB]
Get:46 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 ttf-bitstream-vera all 1.10-8 [352 kB]
Get:47 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-matplotlib-data all 1.5.1-1ubuntu1 [2.414 kB]
Get:48 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-pyparsing all 2.0.3+dfsg1-1ubuntu0.1 [35,4 kB]
Get:49 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-tz all 2014.10~dfsg1-0ubuntu2 [31,5 kB]
Get:50 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-numpy amd64 1:1.11.0-1ubuntu1 [1.763 kB]
Get:51 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-matplotlib amd64 1.5.1-1ubuntu1 [3.888 kB]
Get:52 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-mpmath all 0.19-3 [387 kB]
Get:53 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-nose all 1.3.7-1 [116 kB]
Get:54 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-numexpr amd64 2.4.3-1ubuntu1 [129 kB]
Get:55 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-openpyxl all 2.3.0-1 [193 kB]
Get:56 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pandas-lib amd64 0.17.1-3ubuntu2 [1.538 kB]
Get:57 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pandas all 0.17.1-3ubuntu2 [2.386 kB]
Get:58 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-patsy all 0.4.1-2 [169 kB]
Get:59 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-py all 1.4.31-1 [62,5 kB]
Get:60 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pyglet all 1.1.4.dfsg-3 [726 kB]
Get:61 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-pytest all 2.8.7-4 [119 kB]
Get:62 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 python-simplejson amd64 3.8.1-1ubuntu2 [60,4 kB]
Get:63 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-sympy all 0.7.6.1-1 [2.252 kB]
Get:64 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-sympy-doc all 0.7.6.1-1 [4.774 kB]
Get:65 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-lib amd64 3.2.2-2 [353 kB]
Get:66 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables-data all 3.2.2-2 [45,3 kB]
Get:67 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-tables all 3.2.2-2 [335 kB]
Get:68 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 python-tk amd64 2.7.12-1~16.04 [26,3 kB]
Get:69 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlrd all 0.9.4-1 [107 kB]
Get:70 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-xlwt all 0.7.5+debian1-1 [83,5 kB]
Get:71 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-scipy amd64 0.17.0-1 [8.733 kB]
Get:72 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-statsmodels-lib amd64 0.6.1-4 [173 kB]
Get:73 http://be.archive.ubuntu.com/ubuntu xenial/universe amd64 python-statsmodels all 0.6.1-4 [2.581 kB]
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Processing triggers for libc-bin (2.23-0ubuntu10) ...
➜ redundans git:(master) ✗ python2 redundans.py -v -i test/*_?.fq.gz -f test/contigs.fa -o test/run1
Options: Namespace(fasta='test/contigs.fa', fastq=['test/5000_1.fq.gz', 'test/5000_2.fq.gz', 'test/600_1.fq.gz', 'test/600_2.fq.gz'], identity=0.51, iters=2, joins=5, limit=0.2, linkratio=0.7, log=', mode 'w' at 0x7f85d1de31e0>, longreads=[], mapq=10, mem=16, minLength=200, nocleaning=True, nogapclosing=True, norearrangements=False, noreduction=True, noscaffolding=True, outdir='test/run1', overlap=0.8, reference='', resume=False, threads=4, tmp='/tmp', usebwa=False, verbose=True)

##################################################
[Mon May 7 11:29:18 2018] Reduction...
#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]
/usr/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
test/run1/contigs.fa 163897 245 66377 40.50 221 90.20 94.854 0 97520 59.50 24 9.80

##################################################
[Mon May 7 11:29:29 2018] Estimating parameters of libraries...
Aligning 19504 mates per library...
Insert size statistics Mates orientation stats
FastQ files read length median mean stdev FF FR RF RR
test/5000_1.fq.gz test/5000_2.fq.gz 50 4998 4990.20 721.47 0 4674 0 0
test/600_1.fq.gz test/600_2.fq.gz 100 599 598.63 47.68 0 10000 0 0

##################################################
[Mon May 7 11:29:29 2018] Scaffolding...
iteration 1.1: test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603
19505 pairs. 17302 passed filtering [88.71%]. 1627 in different contigs [8.34%].
1526 pairs. 558 in different contigs [36.57%].
iteration 1.2: test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536
19505 pairs. 17607 passed filtering [90.27%]. 182 in different contigs [0.93%].
1077 pairs. 124 in different contigs [11.51%].
iteration 2.1: test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536
19505 pairs. 15112 passed filtering [77.48%]. 1295 in different contigs [6.64%].
3417 pairs. 396 in different contigs [11.59%].
iteration 2.2: test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
19505 pairs. 15152 passed filtering [77.68%]. 0 in different contigs [0.00%].
3398 pairs. 0 in different contigs [0.00%].

##################################################
[Mon May 7 11:29:34 2018] Gap closing...
iteration 1.1: test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133

##################################################
[Mon May 7 11:29:35 2018] Final reduction...
#file name genome size contigs heterozygous size [%] heterozygous contigs [%] identity [%] possible joins homozygous size [%] homozygous contigs [%]
[WARNING] Nothing reduced!
test/run1/scaffolds.filled.fa 99390 1 0 0.00 0 0.00 0.000 0 99390 100.00 1 100.00

##################################################
[Mon May 7 11:29:35 2018] Reporting statistics...
#fname contigs bases GC [%] contigs >1kb bases in contigs >1kb N50 N90 Ns longest
test/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603
test/run1/contigs.fa 245 163897 40.298 24 117391 3975 233 0 29603
test/run1/contigs.reduced.fa 24 97520 39.355 17 94157 7321 2195 0 29603
test/run1/_sspace.1.1.fa 3 97626 39.344 3 97626 87536 6063 821 87536
test/run1/_sspace.1.2.fa 3 97626 39.344 3 97626 87536 6063 821 87536
test/run1/_sspace.2.1.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/_sspace.2.2.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/scaffolds.fa 1 99133 39.344 1 99133 99133 99133 2328 99133
test/run1/_gapcloser.1.1.fa 1 99390 39.689 1 99390 99390 99390 2 99390
test/run1/scaffolds.filled.fa 1 99390 39.689 1 99390 99390 99390 2 99390
test/run1/scaffolds.reduced.fa 1 99390 39.689 1 99390 99390 99390 2 99390

##################################################
[Mon May 7 11:29:35 2018] Cleaning-up...
#Time elapsed: 0:00:17.376924

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

Introduction to phylogenies in R

Abhi — Wed, 13 Oct 2021 02:27:21 -0500

R phylogenetics is built on the contributed packages for phylogenetics in R, and there are many such packages. Let's begin today by installing a few critical packages, such as ape, phangorn, phytools, and geiger. To get the most recent CRAN version of these packages, you will need to have R 3.3.x installed on your computer!

Address of the bookmark: http://www.phytools.org/Cordoba2017/ex/2/Intro-to-phylogenies.html

Interesting Bioinformatics Resources !

Abhi — Fri, 11 Nov 2022 06:30:46 -0600

1. a reproducible workflow. https://www.youtube.com/watch?v=s3JldKoA0zw This two minute video will change your mind on reproducible research

2. Parallel sequencing lives, or what makes large sequencing projects successful https://academic.oup.com/gigascience/article/6/11/gix100/4557140?login=false

3. Common-sense approaches to sharing tabular data alongside publication https://www.sciencedirect.com/science/article/pii/S2666389921002300

4. A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker https://psyarxiv.com/8xzqy/

5. Practical Computational Reproducibility in the Life Sciences https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30140-6

6. A video by Dr.Keith A. Baggerly from MD Anderson [The Importance of Reproducible Research in High-Throughput Biology](https://www.youtube.com/watch?v=7gYIs7uYbMo) highly recommended.

7. Ten Simple Rules for Reproducible Computational Research http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285)

8. Good Enough Practices in Scientific Computing http://arxiv.org/abs/1609.00037

9. Best Practices for Scientific Computing https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745

10. A Quick Guide to Organizing Computational Biology Projects http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.100042 A must read for computational biologists!

11. Reproducibility of computational workflows is automated using continuous analysis https://www.nature.com/articles/nbt.3780

12. Five selfish reasons to work reproducibly https://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0850-7