• paired-end (PE) and/or mate-pair libraries (NGS-based mode)
• long reads (NGS-based mode)
• synteny to the genome of some related species (reference-based mode)

Scaffolding 

In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.

Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:

• matches not satisfying cut-offs (--identity and --overlap)
• suboptimal matches (only best match of each query to reference is kept)
• and removing overlapping matches on reference.

In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on C. parapsilosis (13 Mb; CANPA) and A. thaliana (119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (Figures in dropbox, CANPA table, ARATH table).
Runs took ~0.5 min for CANPA on 4 CPUs and ~2 min for ARATH on 16 CPUs.

Important remarks:

• Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.
• pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no de novo assembler / scaffolder is perfect...), which breaks synteny.
• pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.
• pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations. Note however, this is experimental implementation!
• Consider closing gaps after scaffolding.

Address of the bookmark: https://github.com/lpryszcz/pyScaf

This project is part of a larger Genome Canada project on genetics and physiology of adaptation to climate change in rainbow trout, and the population genomics component is in the labs of Eric Taylor and Michael Whitlock. The landscape genomics component primarily involves whole genome sequencing approaches to understanding the genomic basis of adaptation to features of habitat, but also to provide insights into phylogeography and the influence of watershed structure on population subdivision in rainbow trout. A PhD in a related field with expertise in basic theory and bioinformatic analysis of population genomics data is required.

The position is available for one year with renewal for up to three additional years. Salary is $55,000 per year plus benefits. To apply, please send a brief cover letter summarizing your qualifications for the position, a CV, and the names, addresses, phone numbers and emails of three references.

Review of applications will begin January 16, 2017. Address application materials to etaylor@zoology.ubc.ca to whom any questions can also be addressed. etaylor@zoology.ubc.ca

Positions available

Applications were invited from for the following posts in an industry sponsored project. The project entitled "OsHK3b technology and Know How", valid for a period upto February, 2018.

Post 3: Senior Research Fellow (Computational Biologist / Metabolic engineering)

Salary: As per DBT rule.

Duration: All the above posts are purely temporary and liable to be terminated at any time without prior notice or ceased/withdrawn by the funding agency.

Age limit: The upper age limit for SRF shall be 32 years, which is relaxed upto 5 years in the case of candidates belonging to Schedule Castes/Schedule Tribes, Women, Physically Handicapped and OBC applicants.

Essential Qualifications: Masters/B Tech/Mtech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building & maintenance, high throughput data handling and analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must. Selection preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.

Desired Skills: Will be expected to manage ongoing research activities in the project, interact with Experimental group, manage the project data analysis, prepare file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.

1. The post applied for must be clearly written on the Envelope containing the application
2. Applications received after last date shall not be entertained, School will not be responsible for any postal delay.
3. No application will be accepted via hand delivery or via e-mail. Please send printed & signed applications with detailed CV on or before 31st January, 2017 by post to the following address:

Prof. Ashwani Pareek
(Project Investigator)
Stress Physiology and Molecular Biology Laboratory (Room No-413),
School of Life Sciences,
Jawaharlal Nehru University,
New Delhi, India – 110067
Email: ashwanipareek@gmail.com

Pondicherry University, Puducherry has been identified as a nodal agency by the Department of Biotechnology, Govt. of India to coordinate this examination along with nine centres namely,

Pune University, Pune;

Anna University, Chennai;

Bose Institute, Kolkata;

Institute of Bioinformatics & Applied Biotechnology, Bangalore;

North-Eastern Hill University, Shillong, University of Hyderabad, Hyderabad;

University of Kerala, Thiruvananthapuram;

Jawaharlal Nehru University, New Delhi and

Assam Agricultural University, Guwahati. 

In the BINC 2015 and 2016 examination, 23 candidates and five candidates were certified respectively. DBT has agreed to fund Research fellowships for all the BINC qualified Indian nationals to pursue Ph.D. in Indian Institutes/Universities.

Note that the candidate must possess a postgraduate degree(or equivalent) & meet the criteria of the institutes/universities in order to avail research fellowship.

In addition, cash prize of Rs. 10,000/- will be awarded to the top 10 BINC qualifiers.

More at http://www.pondiuni.edu.in/exams/binc/

Candidates interested in the position should contact me in advance by email to: g.stracquadanio@essex.ac.uk

The deadline for the application is 28/02/2017; info about the application can be found on the Essex CSEE website.

With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widley accepted and used to store variants detected. The Cancer Genome Atlas Project has seqenced over 30 different cancers with sample size of each cancer type being over 200. The resulting data consisting of genetic variants is stored in the form of Mutation Annotation Format. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner either from TCGA sources or any in-house studies as long as the data is in MAF format. Maftools can also handle ICGC Simple Somatic Mutation format.

maftools is on bioRxiv

Please cite the below if you find this tool useful for you.

Mayakonda, A. and H.P. Koeffler, Maftools: Efficient analysis, visualization and summarization of MAF files from large-scale cohort based cancer studies. bioRxiv, 2016. doi: http://dx.doi.org/10.1101/052662

Address of the bookmark: https://github.com/PoisonAlien/maftools

http://www.bx.psu.edu/~ratan/

Address of the bookmark: http://www.bx.psu.edu/miller_lab/

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge in computer programming, LINUX OS.
Expertise in use of R/other Bioinformatics software

More at http://iasri.res.in/employment/2017/cabin_advertisement_RA_SRF_YP_Mar2017.pdf

Phenomics of Moisture Deficit Stress Tolerance and Nitrogen Use December 31, 2019

Research Associate (RA) Two (2)

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent or System Administrator/ Computer expert for database development, development of phenome data bank and virtual phenomics facility, data archiving and Efficiency in Rice and Wheat-Phase II (Funded by National Agricultural Science Fund, ICAR) Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements. maintenance; Development of image analysis algorithms, APIs and IAPs.

Knowledge in System Biology/ Statistical and computational Genomics/ Bioinformatics
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
December 31, 2019

Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science / Computer Application or equivalent or Master’s in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application or equivalent with 4 years or 5 years of Bachelor’s degree having 1st Division or 60% marks or equivalent overall grade point average, with at least two years of research experience as evidenced from fellowship/ associateship/ training/ other engagements.

Knowledge of Statistical and Computational Genomics/ Bioinformatics.
Knowledge of programming in LINUX/R/Perl/JAVA/PHP/JSP and use of various software & tools.
March 31, 2020

Address of the bookmark: https://github.com/marbl/Krona/wiki

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