Name of the Project : Network Project on Agricultural Bioinformatics Number of positions One
Qualifications : Ph.D Degree in Bioinformatics/Biotechnology/ Biochemistry/Genetics & Breeding/Life Sciences OR Master’s Degree in relevant subject with at least 2 years research experience. Desirable : Working experience in Molecular Biology/Genomics/Bioinformatics, specifically, sequence data analysis using software’s proficiently

Emoluments : Masters Degree Holders Rs. 38,000/- per month Doctoral Degree Holders Rs. 40,000/- per month

Emoluments : Rs.25000/- per month for 1st and 2nd year and Rs. 28000/- per month for 3rd year
Age Limit : Upper age limit is 35 years for men and 40 years for women on the date of interview. Age relaxation for SC/ST and OBC candidates as per rules

More at http://www.cirb.res.in/attachments/195_walk-in-interview%20for%20contractual%20positions%20of%20RA%20and%20SRF%20%28On%20Dated%2011.8.2015%29.pdf

Address of the bookmark: https://github.com/imgag/ClinCNV

Interested candidates may appear before the interview board on 23 February, 2015 at the Office of the Head, Department of Molecular Biology & Biotechnology, Tezpur University with original documents and photocopies of marks sheets, certificates, testimonials, caste certificate (if applicable), experience certificate and a copy of curriculum vitae (CV) duly signed by the candidate.

Position: One (01) Research Associate.

Educational Qualification: Candidates having Ph.D. degree or submitted thesis in any topic of Life Science Areas (Zoology, Botany, Microbiology, Biotechnology etc.) along with knowledge of gene and protein sequence analysis may apply.

Remuneration: Rs. 22,000/- (Rupees twenty two thousand) only + 10% HRA as admissible per month for the first year and Rs. 23,000/- (Rupees twenty three thousand) only + 10% HRA as admissible per month for the second year.

Age: Candidate preferably below the age of 40 years who have obtained a doctorate (Ph.D.) degree from a recognized University.

Upper age limit may be relaxed up to 5 years in the case of candidates belonging SC/ST/OBC/Women and physically challenged.

Position: One (01) Project Assistant.

Educational Qualification: B.Sc./B.Tech./B.E./B.Pharma in any branch with minimum 55% mark in the qualifying examinations and minimum 50 % mark in 10th and 10+2 Science examinations.

Remuneration: Rs. 8,000/- (Rupees eight thousand) only per month (consolidated). Age: Candidate should not be more than 28 years of age on the date of interview. Upper age limit may be relaxed up to 5 years in the case of candidate belonging to SC/ST/OBC/Women/Physically Challenged.

Duration: One year or till completion of the project, whichever is earlier. N.B. No TA/DA will be paid to the candidates for attending the interview.

For further information contact – Dr. Suvendra Kumar Ray, Associate Professor Email: suven@tezu.ernet.in Department of Molecular Biology and Biotechnology Tezpur University Sd/- Dean, Research & Development Tezpur University

Advertisement: http://www.tezu.ernet.in/ProjectWalkin/Advt-SKR2-5342-A.pdf

Title of the Project
Research Associate
(One position)
DBTs Biotechnology/Bioinformatics training centre
PI Dr. Ashok Varma

Duration of the Project Six Months from the date of appointment, can be extended further for six month.

Date & Time: 17th February, 2015 at 10.00 a.m.

Venue: Meeting Room, 3rd floor, Khanolkar Shodhika, ACTREC

Essential Qualifications and Experience:

Ph.D. Degree in Basic Sciences from recognized University. Research experience in Bioinformatics or on gene cloning, protein purification, and crystallization.

*M.Sc. degree obtained after a one year course will not be considered.

Selected candidate will have to join at the earliest.

Consolidated Salary: Rs.28,600/- p.m. {Rs.22,000/- + 30% HRA}

The work progress of the candidate will be monitored and extension after 6 months will depend on satisfactory progress of the work.

Candidates fulfilling these requirements should pre-register by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to ‘program.office@actrec.gov.in’ latest by 17.00 hrs on 12-02-2015.
The interviews would be held on 17th February, 2015 and will be only for the pre-registered candidates. Candidates should report between 09.30 to 10.00 a.m. in Steno Pool, 3rd floor, Khanolkar Shodhika, ACTREC, Kharghar, Navi Mumbai.
No T.A./D.A. will be admissible for attending the interview.

At the time of Interview the candidate should bring original certificates along with CV with contact details of 2 referees and submit the photocopies (attested) of the certificates, with a recent passport size photograph.

All correspondence should be strictly made only to ‘program.office@actrec.gov.in’ as indicated.

Advertisement: www.actrec.gov.in/data%20files/2015/AV-RA-DBT-28-1-15.docx

• Filters SNVs from any variant caller to remove false positives
• Calculates metrics based on BAM files and provides filtering not possible with other tools
• Fully user-configurable filtering (including which filters to use and their thresholds)
• Option to use filters identical to ICGC recommendations

FiNGS provides researchers with a tool to reproducibly filter somatic variants that is simple to both deploy and use, with filters and thresholds that are fully configurable by the user. It ingests and emits standard variant call format (VCF) files and will slot into existing sequencing pipelines. It allows users to develop and implement their own filtering strategies and simple sharing of these with others.

FiNGS reliably improves upon the precision of default variant caller outputs and performs better than other tools designed for the same task.

Address of the bookmark: https://github.com/cpwardell/FiNGS

Who you are
You’re someone who wants to influence your own development. You’re looking for a company where you have the opportunity to pursue your interests across functions and geographies. Where a job title is not considered the final definition of who you are, but the starting point.

Qualifications:
Major: Bioinformatcis or biology major who is interested and wants to learn Biocomputing, At least 2 years of college.
Basic knowledge of LINUX and programming, e.g., perl, python, XML.

More at http://www.roche.com/careers/jobs/jobsearch/job.htm?id=E-00437679&locale=en&title=Summer%20Intern%20-%20Research%20Bioinformatics

Variant calling and/or genotyping

• DiscoSNP++ and discoSnpRAD: Reference-free small variant discovery (SNPs and indels)
• MindTheGap: Detection and assembly of large insertion variants
• TakeABreak: reference-free inversion discovery tool
• SVJedi: Structural Variant genotyper with long read data
• SVJedi-graph: Structural Variant genotyper with long read data using a variation graph

Sequence assembly

• MinYS: reference-guided genome assembly in metagenomics data
• MTG-link: local assembly tool for linked-read data
• Minia: De novo short read assembler
• de-novo pipeline: de-novo assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes
• Mapsembler2: Targeted assembly (not maintained)

Managing k-mers & indexation

• findere: simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
  • fimpera extends findere adding the abundance information.
• kmtricks: modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.
• kmindex is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.
• back to sequences: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.
• Backpack Quotient Filter: k-mer indexing data structure with abundance
• short read connector: Detect similar reads from potentially large read set
• DSK: Count K-mer in sequences

Pangenome graph manipulation

• Pancat: Pangenome Comparison and Analysis Toolkit
• GFAGraphs: a Python library to handle pangenome graph files in GFA format.

Comparative metagenomics with k-mers

• Simka and SimkaMin: Comparative metagenomics for large-scale datasets
• Comparead & Commet: comparison of metagenomic datasets

Species and bacterial strains identification

• ORI: software using long nanopore reads to identify bacteria present in a sample at the strain level
• StrainFLAIR: STRAIN-level proFiLing using vArIation gRaph

General-purpose sequencing data manipulation

• GASSST: long read mapper
• Leon: short read compressor (now included in GATB-core)
• Bloocoo: short read corrector
• BCALM: Construct compacted de Bruijn graphs (unitigs)

 Protein Structure

• A_Purva: Contact Map Overlap solver
• MD-Jeep: Distance Geometry solver
• CSA: Comparative Structural Alignment

Workflow

• SLICEE: parallel execution of bioinformatics workflows

Comparative Genomics

• CASSIS: detection of rearrangement breakpoints
• PLAST: intensive bank-to-bank sequence comparison
• DRJBreakpointFinder: detection and precise localization of excision sites in proviral segments

Name of the Scheme : Distributed Information Sub Centre – DISC

Qualifications : M.Sc/ B Tech in Bioinformatics with NET/GATE or M Tech in Bioinformatics

Number of posts : One

Emoluments : Rs. 25,000/-

Upper age limit : 35 years for Men & 40 years for Women as on date of Interview
How to apply

Date of Interview : 12-03-2015 at 10.00 AM. All relevant certificates (in original) and bio data, No objection certificate in case he/she is employed elsewhere and experience certificate in original (if any) need to be produced at the time of interview.

More at http://spices.res.in/index.php?option=com_content&view=article&id=263

• Whole-genome sequencing
• Whole-exome sequencing
• RNA-seq (speical mode available)
• ChIP-seq

Address of the bookmark: http://qualimap.bioinfo.cipf.es/

This is a short post giving steps on how to actually install R packages. Let’s suppose you want to install the ggplot2 package. Well nothing could be easier. We just fire up an R shell and type:

> install.packages("ggplot2")

In theory the package should just install, however:

• if you are using Linux and don’t have root access, this command won’t work.
• you will be asked to select your local mirror, i.e. which server should you use to download the package.

Installing packages without root access

First, you need to designate a directory where you will store the downloaded packages. On my machine, I use the directory /data/Rpackages/ After creating a package directory, to install a package we use the command:

> install.packages("ggplot2", lib="/data/Rpackages/")
> library(ggplot2, lib.loc="/data/Rpackages/")


It’s a bit of a pain having to type /data/Rpackages/ all the time. To avoid this burden,  we create a file .Renviron in our home area, and add the line R_LIBS=/data/Rpackages/ to it. This means that whenever you start R, the directory /data/Rpackages/ is added to the list of places to look for R packages and so:

> install.packages("ggplot2")
> library(ggplot2)

just works!

Setting the repository

Every time you install a R package, you are asked which repository R should use. To set the repository and avoid having to specify this at every package install, simply:

• create a file .Rprofile in your home area.
• Add the following piece of code to it:


cat(".Rprofile: Setting UK repositoryn")
r = getOption("repos") # hard code the UK repo for CRAN
r["CRAN"] = "http://cran.uk.r-project.org"
options(repos = r)
rm(r)


I found this tip in a stackoverflow answer .