BOL: Related items

Scientists post at Monsanto

Wed, 11 May 2016 07:58:44 -0500

Sustainable agriculture is at the core of Monsanto. We develop technologies that enable farmers to produce more crops while conserving natural resources. Monsanto scientists are conducting research and development (R&D) to revolutionize plant breeding and biotechnology.

Monsanto is seeking a very talented Genomics Scientistto become an integral member of our Global Pipeline Analytics team with a focus on quantitative genetics. The ideal candidate will have familiarity with modeling and analysis of genetic data sets using a variety of statistical techniques.

Major Responsibilities:
- Provide guidance on experimental design for genomic-related experiments
- Familiarity with analysis of the following methods: GWS, QTL, eQTL, RNA-Seq
- Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.
- Ensure timely delivery and clear communication of results
- Develop strong and successful collaborations among various Monsanto enabling teams.

Required Skills:

- PhD degree in Statistics, Biostatistics, Statistical Genetics, Quantitative Genetics, Breeding, Bioinformatics or a related field with 2 years of experience
- Working knowledge and experience with one of the following quantitative languages:R, Python, Perl, SAS
- Background in Windows and Linux operating systems
- Very strong problem solving skills will be required to work well as a member of a dynamic team
- Strong verbal and written communication skills.
- Demonstrated ability to deliver timely results and be results oriented.
- Extensive knowledge of quantitative genetics and experimental design.
- Demonstrated track record of solving challenging and complex problems.

Desired Skills/Experience:

- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines.
- Experience in agronomy and/or plant breeding in vegetables or row crops.

Please apply to
https://jobs.monsanto.com/job/st-louis/genomics-scientist/769/2081771

Sample BINC question paper 2016 - part2

Radha Agarkar — Fri, 13 May 2016 03:42:56 -0500

Download the sample question paper for BINC 2016 - paer II

ORFfinder with smart BLAST

Jit — Tue, 17 May 2016 01:43:15 -0500

ORF Finder

ORFfinder is a graphical analysis tool for finding open reading frames (ORFs). We’ve been working on a few updates, and we’d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.

Smart BLAST (https://ncbiinsights.ncbi.nlm.nih.gov/2015/07/29/smartblast/)

Select one or a group of ORFs and BLAST several databases at once, and use the newly developed SmartBLAST to verify protein names. Looking for the traditional results from BLAST? They’re there too.

MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping

Neel — Fri, 20 May 2016 18:53:49 -0500

MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581

Senior Project Fellow Bioinformatics at NBRI

Sat, 21 May 2016 21:01:05 -0500

Walk In Interview No. 03/Project/2016
Senior Project Fellow Bioinformatics Job vacancies in CSIR- National Botanical Research Institute (NBRI), Lucknow
Area III: Molecular Biology & Biotechnology
Qualification : 1st Class M.Sc. in Bioinformatics/Biotechnology/ Life Science /Biochemistry/Botany with 2 years research experience and at least one publication in SCI Journal or 1st class M.Tech in Bioinformatics
Age : 32 years
Salary : Rs.18000
How to apply
Date & Venue of Interview For Area III: 27-05-2016 at 11.00 A.M. at Conference Room, T.N. Khushoo Block, NBRI, Lucknow.

http://www.nbri.res.in/temp.php

Cytoscape

Anjana — Mon, 23 May 2016 02:32:00 -0500

Cytoscape is an open source software platform for visualizing complex networks and integrating these with any type of attribute data. A lot of Apps are available for various kinds of problem domains, including bioinformatics, social network analysis, and semantic web.

Address of the bookmark: http://www.cytoscape.org/

RA at UNIVERSITY OF HYDERABAD

Sun, 29 May 2016 11:50:37 -0500

UNIVERSITY OF HYDERABAD

School of Life Sciences

Department of Animal Biology

Applications are invited on a plane paper (along with copies of educational qualifications and experience) from eligible candidates for the selection of following position to work under a collaborative research project entitled “Development and application of high resolution genome conformation capture technology to investigate genome architecture in space and time” between University of Hyderabad and CR Rao advanced Institute of Mathematics, Statistics and Computer Sciences, sponsored by Department of Biotechnology, Government of India, New Delhi

Name and No. of positions JRF‐ONE

Emoluments for the position Rs. 25,000/p.m. + Eligible HRA

Qualifications MSc or M.Tech in any branch of biology/bioinformatics/computational biology/computer sciences/Mathematics/Physics

Duration Appointments are made initially for ONE year and can be extended further TWO years or until the duration of project

Our laboratory is interested in understanding signalling and spatiotemporal dynamics of 3‐Dimensional genome architecture and gene expression during embryonic stem cell differentiation by utilizing a combination of cellular, molecular genetics, Biochemical and computational tools in combination with next generation sequencing based chromatin structure analysing methods. Successful candidates shall pursue project related to either experimental or computational analysis of genome and Epigenomics data derived from human and mouse cells. Experience in Computational biology, bioinformatics, statistics, machine learning and algorithmic development is required. Knowledge of programming languages (e.g. C, C++, Perl, Python, Ruby etc.) and statistical framework (e.g. R, matlab, etc.) is preferable. Basic understanding of molecular biology will be an added advantage.

Interested candidates with the above mentioned qualification can send their curriculum vitae to Dr. K. Sreenivasulu, Department of Animal Biology, School of Life Sciences, South campus, University of Hyderabad or via email at positionssklab@gmail.com or svksl@uohyd.ernet.in.

Candidates with CSIR/UGC/ICMR/DBT/BINC qualifications if interested in above mentioned area of research are welcomed to approch principal investigator for a position leading to PhD. Last date for submission of applications is 17/06/2016. Eligible candidates will be called for an interview and they should carry all original certificates of the qualifying exam. No TA/ DA will be paid for attending the interview or at the time of joining the post.

Advertisement: http://www.uohyd.ac.in/images/recruitment/jrf_260516.pdf

HistoneDB 2.0 – with variants

Anjana — Fri, 03 Jun 2016 05:06:20 -0500

This histone database can be used to explore the diversity of histone proteins and their sequence variants in many organisms. The resource was established to better understand how sequence variation may affect functional and structural features of nucleosomes. To get started, select a histone type to explore its variants.

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

BBMap/BBTools package: Multipurpose tool designed for converting reads or other nucleotide data between different formats.

Jit — Mon, 13 Jun 2016 05:47:21 -0500

Reformatis a member of the BBMap/BBTools package. It is a multipurpose tool designed for converting reads or other nucleotide data between different formats. It supports, and can inter-convert:

fastq
fasta
fasta+qual
sam
scarf (an old Illumina format)
bam (if samtools is installed)
gzip
zip
ascii-33 (sanger)
ascii-64 (old Illumina)
paired files
interleaved files

It is multithreaded and can process data at over 500 megabytes per second, and can accept streams from standard in and write to standard out, allowing it to be easily dropped into the middle of a pipeline for format conversion. Reformat autodetects formats based on file extensions and content, making it very easy to use; and the autodetection can be overridden, allowing flexibility for people who don't like to follow naming conventions, or out-of-spec fastq files with qualities values like -17 or 120.

The program has been gradually expanded, and can now perform various other functions. None of these will break pairing, if the input is paired.

Quality trimming (either or both ends)
Quality filtering
Fixed-length trimming
Generation of histograms (base composition, quality, etc)
Subsampling (to a fraction of input reads, or an exact number of reads or bases)
Changing fasta line-wrapping length
Reverse-complementing (all reads or only read 2)
Adding /1 and /2 suffix to read names
GC-content filtering
Length-filtering
Testing for corrupted interleaved files

Reformat is compatible with any platform that supports Java 1.7 or higher. It also has a bash shellscript for simpler invocation. Typical usage examples:

Reformat fastq into fasta:
reformat.sh in=x.fq out=y.fa

Interleave paired reads:
reformat.sh in1=x1.fq in2=x2.fq out=y.fq

Note - you can actually use a shortcut if paired read files have the same name with a 1 and a 2. This is equivalent to the above command:
reformat.sh in=x#.fq out=y.fq

De-interleave reads:
reformat.sh in=x.fq out1=y1.fq out2=y2.fq

Verify that interleaving appears correct, assuming Illumina namimg conventions:
reformat.sh in=x.fq vint

Convert ASCII-33 to ASCII-64:
reformat.sh in=x.fq out=y.fq qin=33 qout=64

Quality-trim paired reads to Q10 on the left and right ends and discard reads shorter than 50bp after trimming:
reformat.sh in1=x1.fq in2=x2.fq out1=y1.fq out2=y2.fq outsingle=singletons.fq qtrim=rl trimq=10 minlength=50

Subsample 10% of the first 20000 pairs in an interleaved file:
reformat.sh in=x.fq out=y.fq reads=20000 samplerate=0.1 int=t
(in this case "int=t" overrides interleaving autodetection, to ensure reads are treated as pairs)

Pipe in a gzipped sam file and pipe out fasta:
reformat.sh in=stdin.sam.gz out=stdout.fa

Reverse-complement reads:
reformat.sh in=x.fq out=y.fq rcomp

For reformatting a file with very long sequences, Reformat will need more memory; just add the additional flag "-Xmx2g". For example, to change the line-wrapping length on the human genome (which has individual sequences over 200Mbp long) to 70 characters:
reformat.sh -Xmx2g in=HG19.fa.gz out=HG19_wrapped.fa.gz fastawrap=70

For additional functions, please run the shellscript with no arguments, or just read it with a text editor. If you have any questions, please post them in this thread.

For people using a non-bash terminal, you may need to type "bash reformat.sh" instead of just "reformat.sh".
For users of Windows or other platforms that do not support bash shellscripts, replace "reformat.sh" with "java -ea -Xmx200m /path/to/bbmap/current/ jgi.ReformatReads"
for example,
java -ea -Xmx200m C:\bbmap\current\ jgi.ReformatReads in=x.fq out=y.fa

Reformat can be downloaded with BBTools here:
https://sourceforge.net/projects/bbmap/

LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines

Jit — Wed, 15 Jun 2016 17:18:36 -0500

LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.

Publication:

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/