Applications are invited for the posts of one Junior Research Fellow in the DBT funded project entitled “Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.

Essential qualifications for JRF: First class M. Sc. / M. Tech in Bioinformatics. Knowledge of programming language, pearl, Statistics and database – HTML, CSS, Java script.

Desirable qualifications: Experience in handling next generation sequencing data

Age limit: 35 years maximum (5 year relaxation for SC/ST and women candidates) Emoluments: 16,000 + 30% HRA.

The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.

Those who are interested in pursuing Ph.D with strong research aptitude are preferred.

Interested candidates may attend the Walk in interview on 25th March 2014 along with the duly filled application forms (format in the following page) with all the relevant documents.

Venue: Division of Nematology, Indian Agricultural Research Institute, New Delhi 110012 (Room No. 306, 3rd floor, LBS building)

Reporting Time: Interested candidates should report strictly between 10.00 to 10.30 AM.

Interview time: 10.30 AM

Short-listed candidates will be called for interview at New Delhi. However, no TA and DA will be paid for attending the interview.

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https://www.iari.res.in/files/JRF_Nema-07032014-20140307-170017.pdf

For more background see also the publication at BMC Bioinformatics.

https://github.com/clwgg/nQuire

Address of the bookmark: https://github.com/clwgg/nQuire

is a state-funded virtual research center aimed at promoting imaging and informatics research infrastructure in South Dakota. BioSNTR research foci include analysis of large-scale genomics and imaging data, application of novel microscopy technologies to study signaling pathways, and identification of new compounds to manipulate signaling pathways.
Responsibilities: This person will be part of Plant Science team with research focus in bioinformatic and molecular network analyses of high throughput data (transcriptomic, proteomic, metabolomics, miRNA). The individual will be integrated into functional genomic projects encompassing grapevine dormancy and freezing tolerance (Fennell) and regulation of soybean nodulation (Subramanian). The successful candidate will perform computational analysis of high throughput, next-generation sequence data and possess the ability to use bioinformatics analytical tools on HPC clusters.

Required Qualifications:
• Ph.D. in plant computational biology or bioinformatics.
• Experience in a high performance computing environment.
• Perl, Python and Java programming experience
• Data management and database development experience

Desired Qualifications:
• Parallel computing experience
• Experience working in a multidisciplinary environment

Contact Information
South Dakota State University
Plant Science
Anne Fennell
anne.fennell@sdstate.edu
Tel. Number: 605-688-6373
http://www.biosntr.org

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

In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it

What is Secure Copy?

scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.

Examples

Copy the file "gene.txt" from a remote host to the local host

    $ scp your_username@remotehost.edu:gene.txt /some/local/directory

Copy the file "foobar.txt" from the local host to a remote host

    $ scp gene.txt your_username@remotehost.edu:/some/remote/directory

Copy the directory "chromosome" from the local host to a remote host's directory "bar"

    $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar

Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"

    $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \
    your_username@rh2.edu:/some/remote/directory/

Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host

    $ scp gene.txt cancer.txt your_username@remotehost.edu:~

Copy the file "gene.txt" from the local host to a remote host using port 2264

    $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory

Copy multiple files from the remote host to your current directory on the local host

    $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .

    $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .

scp Performance

By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.

    $ scp -c blowfish some_file your_username@remotehost.edu:~

It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:

    $ scp -c blowfish -C local_file your_username@remotehost.edu:~

https://github.com/CSB5/lofreq

http://csb5.github.io/lofreq/installation/

https://github.com/CSB5/lofreq/tree/master/dist

Address of the bookmark: http://csb5.github.io/lofreq/

We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.

Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:

Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.

Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.

Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.

Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.

Contact:
Dr. Ravi Sirdeshmukh
Distinguished Scientist & Associate Director, IOB,
Principal Advisor MSMC/MSCTR

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• 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

(A) Senior Research Fellow (One Post): Emoluments as per DST/DBT norms.

Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.

The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.

Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.

Note: ONLY hard copy of the application in the given format will be accepted.

Last date April 03, 2014

Dr. Mukesh Jain
Staff Scientist
National Institute of Plant Genome Research
Aruna Asaf Ali Marg, P.O. Box NO. 10531,
New Delhi - 110067

Advertisement: http://www.nipgr.res.in/careers/vacancies_latest.php#

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