BOL: Related items

Cerulean: A hybrid assembly using high throughput short and long reads

Rahul Nayak — Tue, 05 Jun 2018 10:10:15 -0500

Cerulean extends contigs assembled using short read datasets like Illumina paired-end reads using long reads like PacBio RS long reads. Cerulean v0.1 has been implemented with bacterial genomes in mind. The method is fully described in Deshpande, V., Fung, E. D., Pham, S., & Bafna, V. (2013). Cerulean: A hybrid assembly using high throughput short and long reads. arXiv preprint arXiv:1307.7933. http://arxiv.org/abs/1307.7933

Address of the bookmark: https://sourceforge.net/projects/ceruleanassembler/

Google Genomics

Tenzin Paul — Thu, 18 Dec 2014 11:05:42 -0600

Explore genetic variation interactively. Compare entire cohorts in seconds with SQL-like queries. Compute transition/transversion ratios, genome-wide association, allelic frequency and more.
Process big genomic data easily. Run batch analyses like principal component analysis and Hardy-Weinberg equilibrium on as many samples as you like, in minutes or hours, with just a little code.
Use Google's infrastructure and big data expertise. Store one genome or a million using Google Genomics and take advantage of the same infrastructure that powers Search, Maps, YouTube, Gmail and Drive.
Support emerging global standards. Google Genomics is implementing the API defined by the Global Alliance for Genomics and Health for visualization, analysis and more. Compliant software can access Google Genomics, local servers, or any other implementation.

Address of the bookmark: https://cloud.google.com/genomics/

Studentship at Nagaland University

Tue, 16 Dec 2014 01:35:00 -0600

Nagaland University
(A Central University Estd. By the Act of Parliament No. 35 of 1989)
Lumami 798 627, Nagaland
DBT Sponsored ‘Bioinformatics Infrastructure Facility’ Centre

Applications in plain paper are invited for the posts of (1) Traineeship (2 Nos.) and (2) Studentship – (2 Nos.) in the DBT funded-Bioinformatics Infrastructure Facility (BIF), Nagaland University, Lumami-798627, Nagaland. Details are given below. Interested candidates may submit the application along with self attested copies of certificates in support of the candidature to Prof. Chitta Ranjan Deb, Coordinator or Dr. L. N. Kakati, Deputy Coordinator, BIF Centre, Nagaland University, Lumami-798627, Nagaland on or before 15th January 2015.

The scanned application with relevant documents may be sent by email attachment to bifnulumami@gmail.com. Shortlisted candidates will be informed by email if called for interview. No TA/DA is admissible for attending the interview.

Traineeship (Two nos.)

Post Graduate degree in any branch of Life Sciences from UGC recognized Universities

Knowledge of computers and bioinformatics

Rs.8000/- p.m. fixed.

6 months

Studentship (Two nos.)

Pursuing Post Graduate degree in any branch of Life Sciences from UGC recognized Universities

Knowledge of computers and bioinformatics

Rs.8000/- p.m. fixed.

6 months

Terms and Conditions:

i) Applicants need to produce all original documents if call for interview.
ii) The posts are purely temporary and the appointment does not confer any entitlement or right over the job and will not be considered as formal service.
iii) No TA & DA will be paid for appearing in the walk-in-interview.
iv) The stipend/salary amount is subject to the sanction of DBT, New Delhi.

Advertisement: http://www.nagauniv.org.in/files/BIF%20Advt.pdf

Hercules: a profile HMM-based hybrid error correction algorithm for long reads

Jit — Mon, 20 Aug 2018 14:14:11 -0500

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several studies require long and accurate reads including de novo assembly, fusion and structural variation detection. In such cases researchers often combine both technologies and the more erroneous long reads are corrected using the short reads. Current approaches rely on various graph based alignment techniques and do not take the error profile of the underlying technology into account. Memory- and time- efficient machine learning algorithms that address these shortcomings have the potential to achieve better and more accurate integration of these two technologies. Results: We designed and developed Hercules, the first machine learning-based long read error correction algorithm. The algorithm models every long read as a profile Hidden Markov Model with respect to the underlying platformtextquoterights error profile. The algorithm learns a posterior transition/emission probability distribution for each long read and uses this to correct errors in these reads. Using datasets from two DNA-seq BAC clones (CH17-157L1 and CH17-227A2), and human brain cerebellum polyA RNA-seq, we show that Hercules-corrected reads have the highest mapping rate among all competing algorithms and highest accuracy when most of the basepairs of a long read are covered with short reads. Availability:

Hercules source code is available at https://github.com/BilkentCompGen/Hercules

Address of the bookmark: https://github.com/BilkentCompGen/Hercules

Senior Scientist (Agricultural Bio-informatics) (One post)

Wed, 24 Dec 2014 05:01:02 -0600

Agricultural Scientists Recruitment Board

Qualifications Essential:
Doctoral degree in Bio-informatics/ Biotechnology/Molecular Biology and Biotechnology/Life Sciences/ Computer Sciences with specialization in Bio-informatics including relevant basic sciences with 8 years’ experience in the relevant subject as Scientist/Lecturer or in an equivalent position in the Pay Band- 3 of 15600-39100 with Grade Pay of 5400/6000/7000/8000 having made contribution to research/teachin/extension education as evidenced by published work/innovations and impact.

Doctoral degree in the above subject(s) including relevant basic sciences with minimum 8 years’ experience of high quality post-doctoral research in an institution/organization as evidenced by at least 6 publications in journals with NAAS rating of 7.5 or above.

Desirable:
(i) Specialization and experience: Knowledge of software development and its application in crop bioinformatics, experience in handling ‘omies’data.
(ii) Teaching experience in relevant subject

The Secretary, Agricultural Scientists Recruitment Board, Indian Council of Agricultural Research Krishi Anusandhan Bhavan-I, Pusa New Delhi –110 012, India

Detailed eligibility criteria with how to apply information can be had at:
http://www.indiastudychannel.com/jobs/333467-Indian-Council-of-Agricultural-Research-looking-for-Assistant-Director-General.aspx

More at http://asrb.org.in/administrator/uploads_dir/1418978057english.pdf

LoRMA: A tool for correcting sequencing errors in long reads

Abhimanyu Singh — Thu, 06 Sep 2018 16:21:01 -0500

An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of k-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75×, the throughput of the new method is at least 20% higher.

conda install -c atgc-montpellier lorma

Address of the bookmark: https://gite.lirmm.fr/lorma/lorma-releases/wikis/home

RStudio

Jitendra Narayan — Sat, 27 Dec 2014 06:50:58 -0600

RStudio IDE is a powerful and productive user interface for R. It’s free and open source, and works great on Windows, Mac, and Linux.

The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.

More at http://www.rstudio.com/

http://www.rstudio.com/products/RStudio/

Address of the bookmark: http://www.rstudio.com/

Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads

Rahul Nayak — Fri, 19 Oct 2018 08:23:42 -0500

Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top–down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom–up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data

Address of the bookmark: https://sourceforge.net/projects/bio-rainbow/files/

Genome assembly tutorial "Genome Assembly for short and long reads"

Jit — Sat, 19 Jan 2019 17:29:53 -0600

In this lab we will perform de novo genome assembly of a bacterial genome. You will be guided through the genome assembly starting with data quality control, through to building contigs and analysis of the results. At the end of the lab you will know:

How to perform basic quality checks on the input data
How to run a short read assembler on Illumina data
How to run a long read assembler on Pacific Biosciences or Oxford Nanopore data
How to improve the accuracy of a long read assembly using short reads
How to assess the quality of an assembly

https://bioinformaticsdotca.github.io/high-throughput_biology_2017

Address of the bookmark: https://bioinformaticsdotca.github.io/high-throughput_biology_2017_module6_lab

Research Associate @ TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI

Thu, 08 Jan 2015 20:53:57 -0600

TATA MEMORIAL CENTRE ADVANCED CENTRE FOR TREATMENT, RESEARCH AND EDUCATION IN CANCER KHARGHAR, NAVI MUMBAI – 410210

Website: www.actrec.gov.in; Ph: 27405000

No. ACTREC/Advt./ 66 /2014 23rd December, 2014
Research Associate

International Cancer Genome Consortium (ICGC) - India Project (IRB Project No. 3 A/c. No. 2408)

Dr. Rajiv Sarin

Duration of the Project: One year Extendable up to Three years.

Consolidated Salary: Rs. 42,000/- p.m.

Application last date: 8th January, 2015.

Interview Date & Time: 21st January, 2015, at 11.00 a.m.

Venue: Conference Room, 3rd floor, Khanolkar Shodhika, ACTREC.

Essential Qualifications and Experience:

Ph.D (any branch of Life Sciences)

The candidate must have at least one year experience after Ph.D., preferably in Genomics and Molecular Biology.

Candidates fulfilling these requirements should pre register themselves by sending their application in the prescribed format with recent CV and contact details of 2 referees by e-mail to icgc@actrec.gov.in latest 8th January, 2015 by 10.00 a.m.

Candidates shortlisted for the interview will be intimated by email on or before 9th January, 2015.

The interviews would be held on 21st January 2015 and will be only for the pre registered candidates who have been shortlisted.
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.

Advertisement: www.actrec.gov.in/data%20files/2014/Walk-in-Research-Fellow-26-12-14.doc