BOL: Related items

Quick next generation sequencing (NGS) terms definition

Neel — Fri, 09 Jun 2017 04:52:26 -0500

fragment size: the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [δmin,δmax]. Most (>90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.

concordant reads: a read pair is called concordant if they can be mapped to the reference genome as “expected”: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.

discordant reads: briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.

split reads: a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).

read depth: number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that “cover” each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).

BIC-PGI Bioinformatics Project Dissertation Program

Fri, 12 Dec 2014 21:17:30 -0600

Biomedical Informatics Centre, PGIMER, Chandigarh invites application for a project dissertation program for students who have completed their first year of M.Sc. in Bioinformatics.

This is an exciting opportunity for Master's students to train in modern methods in Bioinformatics. The duration of the training will be four to six months, starting from January 2015.

Education: Pursuing M.Sc. Bioinformatics

Essential: Post graduate applicants should have completed their first year and should be in the third semester or first half of the second year.

Only students who are willing to spend a minimum period of 4 months to a maximum of six months, without any break, would be eligible for the program.

How to Apply: Candidates interested in the above project dissertation program should apply online.

Send your CV, Scanned copy of letter of recommendation from Head of Institution along with Registration form in the given format should be sent to: info@bicpgi.org

Please mention clearly “Project dissertation & your Name” in the Subject.

The last date for application is December 31, 2014

Note: Selected candidates may please note that the program is free of cost and would not provide any financial aid for transport and stay.

Name of the selected candidates would be posted on the centre website by December 31, 2014. Incomplete applications will be rejected.

For more information visit our website: http://www.bic-pgi.org/project_dissertation.pdf

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

HALC: High throughput algorithm for long read error correction

Jit — Fri, 08 Jun 2018 10:47:41 -0500

HALC, a high throughput algorithm for long read error correction. HALC aligns the long reads to short read contigs from the same species with a relatively low identity requirement so that a long read region can be aligned to at least one contig region, including its true genome region’s repeats in the contigs sufficiently similar to it (similar repeat based alignment approach) HALC was able to obtain 6.7-41.1% higher throughput than the existing algorithms while maintaining comparable accuracy. The HALC corrected long reads can thus result in 11.4-60.7% longer assembled contigs than the existing algorithms.

Address of the bookmark: https://github.com/lanl001/halc

nanofilt: Filtering and trimming of long read sequencing data

Jit — Mon, 30 Jul 2018 12:01:52 -0500

Filtering on quality and/or read length, and optional trimming after passing filters.
Reads from stdin, writes to stdout.

Intended to be used:

directly after fastq extraction
prior to mapping
in a stream between extraction and mapping

https://github.com/wdecoster/nanofilt

Address of the bookmark: https://github.com/wdecoster/nanofilt

Bioinformatics Scientist at ICAR Labs

Sun, 21 Dec 2014 23:47:03 -0600

AGRICUL AGRICULTURAL SCIENTISTS RECRUITMENT BOARD TURAL SCIENTISTS RECRUITMENT BOARD
KRISHI ANUSANDHAN BHAVAN-I, PUSA, NEW DELHI-110 012

ADVERTISEMENT NO. 03/2014

PRINCIPAL SCIENTIST

Pay Band: Minimum pay of `43,000 in the PB-4 of `37400-67000/- + RGP of `10,000/-.

Age: The candidates must not have attained the age of 52 years as on 19.01.2015. There shall be no age limit for the Council’s employees.

ICAR-Indian Institute for Agricultural Biotechnology, (IIAB) Ranchi (Jharkhand)

151. Principal Scientist (Bioinformatics) (One post)

SENIOR SCIENTIST/PROGRAMME COORDINATOR

Pay Band: PB-4 of ` 37400-67000/- + RGP of ` 9,000/-.

Age: The candidates must not have attained the age of 47 years as on 19.01.2015. There shall be no age limit for the Council’s employees.

National Institute of Biotic Stress Management, Raipur (Chhattishgarh)

166. Senior Scientist (Bioinformatics) (One post)

IMPORTANT NOTE
I. (i) CLOSING DATE

THE CLOSING DATE FOR RECEIPT OF APPLICATIONS IN AGRICULTURAL SCIENTISTS RECRUITMENT BOARD IS 19.01.2015 (For applications posted from abroad and in the Andaman and Nicobar Islands, Lakshdweep, Minicoy and Amindivi islands, States/ Union Territories in the North-Eastern Region, Ladakh Division of J & K State, Sikkim, Pangi, Sub-division of Chamba, Lahul and Spiti Districts of Himachal Pradesh, the last date for receipt of application will be 02.02.2015). Non receipt of the application by the closing date will result in rejection of the application.

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

nQuire: A statistical framework for ploidy estimation using NGS short-read data

Jit — Thu, 31 Jan 2019 05:12:19 -0600

nQuire implements a set of commands to estimate ploidy level of individuals from species, where recent polyploidization occurred and intraspecific ploidy variation is observed. Specifically, nQuire uses next-generation sequencing data to distinguish between diploids, triploids and tetraploids, on the basis of frequency distributions at variant sites where only two bases are segregating.

For more background see also the publication at BMC Bioinformatics.

https://github.com/clwgg/nQuire

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

Which of the followings are the best place to study Bioinformatics ?

Reshma Khatun — Sun, 28 Dec 2014 00:20:30 -0600

Bioinformatics is a major growth area and qualified Bioinformaticians are in high demand. An explosion in biological data has resulted from genome projects, next generation sequencing and other 'omics' techniques. Bioinformatics provides the tools to analyse and exploit such data sets.

Can you please suggest me the best place to study bioinformatics ( Grad/PostGrad).

gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output

Rahul Nayak — Fri, 24 Jan 2020 06:04:40 -0600

gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser.

gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

Roche has acquired Bina Technologies !!!

Jit — Tue, 30 Dec 2014 09:42:16 -0600

Bina Technologies is a privately held company that provides a big data platform for centralized management and processing of next generation sequencing (NGS) data for the academic and translational research markets. Bina will be integrated into the Roche Sequencing Unit, and will continue to focus on development of their innovative genomic analysis solution.

Roche has acquired Bina Technologies, a privately-owned biotech company based in California. The biotech’s first product was the Bina Box, a platform for secondary genomic analysis, sequence alignment, and variant calling, but since 2012, it has developed other products and platforms.

It is our shared vision with Roche that informatics and data sciences are critical elements of an end-to-end genomics solution. Fast, easy-to-use, scalable, and robust informatics solutions make a big difference in the quality and impact of the work of scientists and researchers. We believe in the future of data-driven, personalized medicine. We are passionate about accelerating that future together with Roche.

Financial details of the deal were not disclosed. For Roche, the move is yet another in a string of acquisitions. Last week (December 18), Roche paid $489 million for antibody maker Dutalys. And earlier this month, Roche bought prenatal testing company Ariosa Diagnostics.

Reference

http://blog.bina.com/news/bina-technologies-acquired-by-roche?&__hssc=109677338.1.1419953400266&__hstc=109677338.b8350f2729889b08f1325906d5236cd3.1419953400266.1419953400266.1419953400266.1&hsCtaTracking=96cac941-9372-4bbf-bacb-3ca6f1ff8cfd|3fce0f18-835b-4086-9345-388880861732

http://www.the-scientist.com/?articles.view/articleNo/41750/title/Roche-Buys-Bioinformatics-Firm/