Lab page @ http://krishna.gs.washington.edu/index.html

Address of the bookmark: https://github.com/dentearl/evolverSimControl

(A) Regulatory System Analysis with respect to microRNAs

(B) Computational Epigenomics & Regulomics:

(C) Computational issues with Next Generation Sequencing:

Department of Biotechnology,
Institute of Himalyan Bioresources Technology
CSIR, Palampur(Himachal Pradesh), India.
Email: ravishihbt.res.in; ravish9gmail.com

More @ http://scbb.ihbt.res.in/SCBB_dept/Lab_Member.php

Following are the genome assembly tools based on string graph:

1.SGA (String Graph Assembler) https://github.com/jts/sga

Assembles large genomes from high coverage short read data. SGA is designed as a modular set of programs, which are used to form an assembly pipeline. SGA implements a set of assembly algorithms based on the FM-index. As the FM-index is a compressed data structure, the algorithms are very memory efficient. The SGA assembly has three distinct phases. The first phase corrects base calling errors in the reads. The second phase assembles contigs from the corrected reads. The third phase uses paired end and/or mate pair data to build scaffolds from the contigs. The output of this software is a PDF report that allows the properties of the genome and data quality to be visually explored. By providing more information to the user at the start of an assembly project, this software will help increase awareness of the factors that make a given assembly easy or difficult, assist in the selection of software and parameters and help to troubleshoot an assembly if it runs into problems.

2. SAGE: String-overlap Assembly of GEnomes https://github.com/lucian-ilie/SAGE2

SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers.

3. FSG: Fast String Graph

The new integrated assembler has been assessed on a standard benchmark, showing that fast string graph (FSG) is significantly faster than SGA while maintaining a moderate use of main memory, and showing practical advantages in running FSG on multiple threads. Moreover, we have studied the effect of coverage rates on the running times.

4.  BASE https://github.com/dhlbh/BASE

It enhances the classic seed-extension approach by indexing the reads efficiently to generate adaptive seeds that have high probability to appear uniquely in the genome. Such seeds form the basis for BASE to build extension trees and then to use reverse validation to remove the branches based on read coverage and paired-end information, resulting in high-quality consensus sequences of reads sharing the seeds. Such consensus sequences are then extended to contigs. BASE is a practically efficient tool for constructing contig, with significant improvement in quality for long NGS reads. It is relatively easy to extend BASE to include scaffolding.

5. Fermi https://github.com/lh3/fermi/

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of unitigs to represent all the information in raw reads.

If you want to learn about String Graph assembler, please read the following papers -

i) The Fragment Assembly String Graph - E. W. Myers

This paper describes the String Graph concept.

ii) Efficient construction of an assembly string graph using the FM-index - Jared T. Simpson and Richard Durbin

This earlier paper from Simpson and Durbin

iii) Efficient de novo assembly of large genomes using compressed data structures - Jared T. Simpson and Richard Durbin

More @ http://www.bioinf.manchester.ac.uk/dbbrowser/index.php

Address of the bookmark: https://mummer4.github.io/

No. ACTREC/Advt./ 72 /2013

WALK IN INTERVIEW

1. JRF*
Genome-wide RNAi screen with human pooled tyrosine kinase shRNA libraries in head and neck squamous call carcinoma (HNSCC) cell lines
DBT A/C No. 3071, Dr. Amit Dutt

2. JRF
IRB Project ACTREC Funds
Dr. Amit Dutt

3. RA
Defining the cancer genome of Head and Neck Squamous Cell Carcinoma (HNSCC) with SNP arrays and next generation sequencing technology
A/C No. 2895, Dr. Amit Dutt

Duration of the Project: One year from the date of appointment, or as and when project terminates.

Consolidated Salary: RA : Rs. 40,000/- p.m.
JRF* (DBT): Rs. 20,800/- p.m.
JRF: Rs. 16,000/- p.m.
Date & Time: 6th November, 2013, at 10.00 a.m.

Venue: Conference Room

Minimum Qualifications and Experience:

RA: The ideal applicant should have a PhD in a relevant field. He/she should have a strong computational biology background, with demonstrated experience in coding using Perl, Python, Java or C++. He/she should be familiar with working in unix enviromnent, devising computational algorithms for data analysis, statistical data analysis in R and matlab and database programming using MySQL. Hands on experience in analyzing high throughput data would be an added advantage.

JRF* (DBT project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Valid UGC-CSIR/DBT/ICMR JRF qualification and laboratory experience in molecular biology. Previous experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team would be desirable.

JRF (ACTREC project): M.Sc. in Life Sciences or M.Tech in Biotechnology with good academic record (Minimum of 60% aggregate). Minimum 2 yrs experience in molecular biology and animal tissue culture with high throughput platforms and ability to work with a large team is essential.

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

Candidates fulfilling above requirements should send their application by e-mail to
‘careers.duttlab@gmail.com. in the format given below so as to reach on or before
4th November, 2013.

Advertisement:

http://www.actrec.gov.in/data%20files/2013/AD-RA-JR-TECHN-6-NOV.pdf

Using AlignGraph

AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]

Address of the bookmark: https://github.com/baoe/AlignGraph

1. Project Junior Research Fellow / Project Assistant

Last Date: 11th Nov 2013

Qualification B.Tech (Comp. Sci.), B.Tech/M.Tech (Bioinformatics), MCA, M.Sc. (Mathematics/Statistics)

Desirable Qualifications: Programming in FORTRAN/ C /PERL, Web application technologies

Upper Age limit 28

Rs.12000 / Rs.16000 (as sanctioned by the funding agency)

General terms and conditions:

Positions are purely temporary and co-terminus with the project.

HRDG (CSIR) prevailing guidelines are applicable these positions.

All categories of applicants are required to submit online application.

Enhancement of stipend to Project JRF to Project SRF will be with the due recommendation of Principal Investigator and approval of the Director on the evaluation of the 3 member Standing Committee consisting of Chairperson at the level of Chief Scientist, Coordinator of the JRFs/RAs/PDFs and the Principal Investigator of the Project.

The age relaxation as per HRDG (CSIR) norms: SC/ST/OBC/Women/Physically Handicapped persons – five years.

The Stipend normally be fixed at Rs.22000/- for Research Associates/Post Doc. Fellows. However, a selected RA/PDF may be placed in the higher start of stipend if there is ample justification and such recommendation is made by the Selection Committee. Based on the recommendation with justification by the PI and approval of the Director, person getting stipend at lower rate may be elevated to higher rate subject to availability of the funds in the project.

Recruitment will be based on initial screening based on qualifications and experience criteria and also based on suitability of the candidates to the nature of research project. This screening will be followed by written test followed / interview. After completing this process, candidates will be shortlisted and appointed in specific project subjects as and when appropriate positions become available. The pool of selected candidates will be valid for six months.

Remunerations indicate are maximum admissible and will depend upon the availability of funds and subject to conditions applicable to projects from different funding agencies at the time of recruitment.

Apply : http://www.ccmb.res.in/positions/projects/temp_positions.php

Form download : http://www.ccmb.res.in/positions/projects/oct-2013/pdf_download.php