BOL: Related items

Scallop: reference-based transcriptome assembler for RNA-seq

Rahul Nayak — Tue, 08 May 2018 04:23:27 -0500

Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.

Scallop paper has been published at Nature Biotechnology. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at scalloptest.

Please also checkout the podcast about Scallop (thanks Roman Cheplyaka for the interview). It is available at both the bioinformatics chat and iTunes.

https://github.com/Kingsford-Group/scallop

Address of the bookmark: https://github.com/Kingsford-Group/scallop

SRF and JRF Bioinformatics at Tezpur University, Napaam

Wed, 03 Aug 2016 03:47:38 -0500

Applications are invited for the following temporary positions unde MHRD sponsored Centre of Excellence
in the Department of Computer Science and Engineering (CSE), Tezpur University

Qualification
and Experience : Senior Research Fellow (SRF) and JRF : First Class in M.E/M.Tech in CSE/IT/ECE with research
experience in relevant fields of research (Candidates having valid GATE/NET Score would be preferred).

Fellowship: Rs. 18,000/- per month (fixed)

Duration : 2 (Two) years and may be extended
depending on status of the project

Age Limit: Candidates should not be more than 32 years of
age in case of SRF and 28 years of age in case of JRF and TA. Upper age limit may be relaxed up to 5
years in the case of candidate belonging to SC/ ST/ OBC/ Women/ Differently abled.

How to Apply:
Interested candidates may send their application on plain paper by post along with his/her educational
qualifications, research experience certificates (for SRF), 02 copies of recent passport/stamp size photographs
and contact phone number to Professor D.K Bhattacharyya, Principal Investigator, Department of Computer
Science & Engineering, Tezpur University, Napaam – 784 028, or mail it to dkb@tezu.ernet.in
(or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.

No TA/DA shall
be paid for attending the interview.

For more details: http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-DKB-20-225-6779-A.pdf

Bioinformatics Scientist – ICMR Computational Genomics Centre

Sat, 26 Dec 2020 10:18:29 -0600

ICMR invites online applications, from Indian Citizens, up to 8th January 2020 till 5:30 PM to fill up the following post to be filled purely on a temporary basis under “ICMR Computational Genomics Centre” under Dr. Harpreet Singh, Head, Division of Biomedical Informatics (BMI), ICMR HQRS, New Delhi 110029.
The Terms & Conditions for the post are as follows:

a) Scientist-B – UR (2 posts-Bioinformatics) on consolidated salary of Rs.48,000/- pm + HRA

b) Scientist C – UR (1 post -Bioinformatics) on consolidated salary of Rs. 51,000 pm+ HRA

c) Scientist B- UR (2 post-Statistics) on a consolidated salary of Rs.48,000/- pm +HRA

d) Computer Programmer 1 post UR & 1 post SC on a consolidated salary of Rs. 32,500/- pm

e) Research Assistant -UR 1 post on a consolidated salary of Rs. 31,000/- pm

More at https://projectjobs.icmr.org.in/sccbioinformatics/uploads/recruitment/Adv_BMI_24122020.pdf

RePS: Repeat-masked Phrap with scaffolding, a WGS sequence assembler

Jit — Sat, 04 Jan 2020 01:08:09 -0600

RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering

More at

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC186573/

Address of the bookmark: ftp://ftp.genomics.org.cn/pub/ricedb/Tools/RePS/RePS-IBM-AIX.tar.gz

Omega2: metagenome assembly pipeline

Jit — Mon, 10 Jul 2017 05:56:07 -0500

Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.

Address of the bookmark: http://omega.omicsbio.org/

Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra

Tue, 30 Aug 2016 04:16:15 -0500

Scientist
Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra
Scientist (One position)
Project: Bioinformatics centre DBT- Sub-DIC at ACTREC
Funding agency: DBT Grant No.232

Duration of the Project: Six Months from the date of appointment can be extended further for six months
Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&D experience in Bioinformatics or relevant subjects from recognized institutes.
OR
Ph.D. degree in Bioinformatics or Life Sciences from recognized University.
M.Sc. degree obtained after a one year course will not be considered.
Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s).

More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx

HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies

Jit — Tue, 15 May 2018 07:35:26 -0500

HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to: NGS short reads (Illumina HiSeq) clone-based sequencing (Fosmid or BAC clones) SMRT reads (PacBio) Oxford Nanopore reads 10X Genomics Linked-Reads proximity-ligation (Hi-C) reads high-coverage sequencing (>40x coverage-per-SNP) using above technologies combinations of the above technologies (e.g. scaffold long reads with Hi-C reads) See below for specific examples of command line options and best practices for some of these technologies. NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants. If you use HapCUT2 in your research, please cite: Edge, P., Bafna, V. & Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116

Address of the bookmark: https://github.com/vibansal/HapCUT2

SWALO: Scaffolding with assembly likelihood optimization

Jit — Wed, 20 Jun 2018 02:45:16 -0500

SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing. Please email your questions, comments, suggestions, and bug reports to atif.bd@gmail.com.

Address of the bookmark: https://atifrahman.github.io/SWALO/

Bioinformatics jobs at Chittaranjan National Cancer Institute

Thu, 29 Sep 2016 09:36:33 -0500

Chittaranjan National Cancer Institute Advertisement No.497/2016 Invites Applications For Senior Scientific Officer, Gr. II

Note: Experience in the following field required: Molecular cancer cytogenetic and genetic toxicology Molecular drug Designing and targeted therapy Cancer genomics, proteomics, bioinformatics and next generation sequencing Therapeutic stem cell research and gene therapy Molecular cancer immunology and immunotherapy Molecular epidemiology Tumor endocrinology Translation research Ultra structural/tissue engg/development biology research Virus and cancer Molecular pathology No. of Posts: 11 (Eleven), (SC-1, OBC-3, UR-7)

Location: Kolkata (Calcutta) Salary: Rs.15600-39100 + Grade, Pay Rs.5400/-

For details kindly refer to the Employment News dated 24-30 September, 2016 and in the Institute’s Website: http://www.cnci.org.in

Last date for receipt of applications is 30 days from the date of notification in the Employment News. Director Chittaranjan National Cancer Institute 378, S.P.

Institute’s Website: http://www.cnci.org.in

IMPUTE2

Jit — Thu, 27 Oct 2016 11:21:44 -0500

IMPUTE2 is a computer program for phasing observed genotypes and imputing missing genotypes. Most people use just a couple of the program's basic functions, but we have also built up a collection of specialized and powerful options. If you are new to IMPUTE2, or indeed to phasing and imputation in general, we suggest that you start by learning the basics.

You should begin by downloading the program from here. You will need to choose the link that matches your computing platform and then follow the instructions for opening the download package.

Once you have done this, you will be ready to try some example analyses on the test data that are provided with the download. The section on Examples shows how to use the most common IMPUTE2 functions. We suggest that you work through these examples and try to understand what the elements of each command are doing. If you don't understand something or would like to know if the program can perform a function that isn't listed, you can read our FAQ or submit a question to our mail list.

When you have learned the basic functionality of the program, you can use several features of this website to prepare your own analysis:

Learn about best practices for imputation.
Download reference data that you can use to impute genotypes in your study.
Look through a complete list of program options.

Address of the bookmark: https://mathgen.stats.ox.ac.uk/impute/impute_v2.html