BOL: Related items

karyoploteR: plot whole genomes with arbitrary data

Abhimanyu Singh — Fri, 02 Feb 2018 03:24:28 -0600

karyoploteR is an R package to create karyoplots, that is, representations of whole genomes with arbitrary data plotted on them. It is inspired by the R base graphics system and does not depend on other graphics packages. The aim of karyoploteR is to offer the user an easy way to plot data along the genome to get broad genome-wide view to facilitate the identification of genome wide relations and distributions.

Address of the bookmark: https://bernatgel.github.io/karyoploter_tutorial/

Research Associate at International Centre for Genetic Engineering and Biotechnology (ICGEB)

Wed, 17 Jun 2015 18:49:05 -0500

Research Associate
International Centre for Genetic Engineering and Biotechnology (ICGEB)
Address: Aruna Asaf Ali Marg, Jawaharlal Nehru University, New Delhi
Postal Code: 110067
City: New Delhi
State: Delhi
Qualifications: Experience in many docking softwares and operating systems is essential. Additional experience in bioinformatics and computational biology tools will be useful.
Details will be available at: http://www.icgeb.org/vacancies.html

How To Apply: Submit curriculum vitae to: sb.icgeb@gmail.com
Last Date: 5 July 2015

GRASS: a generic algorithm for scaffolding next-generation sequencing assemblies.

Abhimanyu Singh — Tue, 23 May 2017 05:20:32 -0500

GRASS (GeneRic ASsembly Scaffolder)-a novel algorithm for scaffolding second-generation sequencing assemblies capable of using diverse information sources. GRASS offers a mixed-integer programming formulation of the contig scaffolding problem, which combines contig order, distance and orientation in a single optimization objective. The resulting optimization problem is solved using an expectation-maximization procedure and an unconstrained binary quadratic programming approximation of the original problem. We compared GRASS with existing HTS scaffolders using Illumina paired reads of three bacterial genomes. Our algorithm constructs a comparable number of scaffolds, but makes fewer errors. This result is further improved when additional data, in the form of related genome sequences, are used.

Address of the bookmark: https://github.com/AlexeyG/GRASS

Research Associate Bioinformatics job position in Indian Agricultural Statistics Research Institute (IASRI), Pusa, New Delhi

Wed, 17 Jun 2015 20:48:40 -0500

Research Associate Statistics

Eligibility : M Phil / Phd, MSc

Location : Delhi

Last Date : 27 Jun 2015

Hiring Process : Walk - In
Indian Agricultural Statistics Research Institute (IASRI) - Job DetailsDate of posting:03 Jun 15

Research Associate Statisticsjob position in Indian Agricultural Statistics Research Institute (IASRI)
on purely contractual temporary basis

Project : “ICAR-Network Project of Transgenic in Crops”

Qualification : Ph.D. in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent OR Post-Graduation in Bioinformatics/ Agricultural Statistics/ Statistics/ Computer Science/ Computer Application/ Life Science/ Biotechnology/ Agricultural Science or equivalent with 1st Division or 60% marks or equivalent with at least two years of research experience.

No.of Post: 01

Emoluments for RA: Consolidated Rs. 24000/- per month + 30% HRA for Ph.D holders and consolidated Rs. 23000/- per month + 30% HRA for Master Degree.

Age Limit : 40 years
How to apply

Walk-in-interview will be held on 27th June 2015, 10.30 A.M at IASRI, Pusa, New Delhi

More at http://iasri.res.in/employment/employment.htm

ICGEB Bioinformatics Research Associate Vacancy

Thu, 25 Jun 2015 20:41:00 -0500

Research Associate Position at ICGEB, New Delhi with Dr. Amit Sharma

Starting 15th July 2015, the position relates to a project specifically for in silico drug docking, screening, design, optimisation and linkage with active chemists.

Experience in many docking softwares and operating systems is essential.

Additional experience in bioinformatics and computational biology tools will be useful.

Submit curriculum vitae to: sb.icgeb@gmail.com

Closing date: 5 July 2015

Ranbow: a haplotype assembler for polyploid genomes

Jit — Fri, 01 Jun 2018 07:21:54 -0500

Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function: ranbow hap: for haplotyping ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads ranbow phylo: for the phylogenetic analysis

Address of the bookmark: https://www.molgen.mpg.de/ranbow

Research Scientist at DuPONT

Fri, 17 Jul 2015 20:36:17 -0500

Research Scientist
Hyderabad, Telangana
Job Description

Job Description

The Global Trait Discovery Informatics (GTDI) group located at the DuPont Knowledge Centre (DKC), Hyderabad, India is currently seeking applications for a highly motivated computational biologist. The GTDI group contributes to research programs in plant biotechnology at the DKC as well as across research centers located in DuPont Pioneer, Johnston, Iowa and at the DuPont Experimental Station in Wilmington, Delaware.

We are looking for candidates who have experience in analysis of high-throughput -omics datasets. The researcher will be primarily responsible for analyzing diverse -omics datatypes, such as transcriptomics, proteomics and metabolomics and actively contribute towards building streamlined solutions.

The candidate will be part of a diverse team of experimental biologists, computational biologists and software developers. A critical aspect of this position involves working with global teams across multiple locations and will require effective project coordination and communication skills. This is an exciting opportunity for candidates with strong data driven skills, who want to work at the interface of computational and experimental biology and contribute towards scientific discovery.

Responsibilities

·Integrate and analyze multiple datatypes in the context of experimental observations with a goal towards formulating testable hypothesis.

·Understanding the research questions from experimental biologists and formulate relevant in silico analyses.

·Establish and implement systematic analysis workflows starting from processing of raw data to biological interpretation.

·Critically analyze a wide variety of experimental data with a view to solving the underlying research questions.

·Identify and generate datasets for scientific testing and evaluation of algorithms.

Qualifications

PhD in computational biology, bioinformatics, population genetics, complex systems, computer sciences or any relevant physical or mathematical sciences, with experience in analyzing diverse -omics datasets.

Job Qualifications

Qualifications

More at http://careers.dupont.com/jobsearch/job-details/research-scientist/006077W-01/

Installing Salmon for Trinity !

Rahul Nayak — Tue, 03 Jul 2018 09:02:29 -0500

➜ trinityrnaseq-Trinity-v2.6.6 git:(master) ✗ conda install salmon
Solving environment: done

## Package Plan ##

environment location: /home/urbe/anaconda3

added / updated specs:
- salmon

The following packages will be downloaded:

package | build
---------------------------|-----------------
boost-1.64.0 | py36_4 331 KB conda-forge
jemalloc-5.1.0 | hfc679d8_0 8.2 MB conda-forge
boost-cpp-1.64.0 | 1 17.8 MB conda-forge
salmon-0.10.2 | 1 3.7 MB bioconda
conda-4.5.5 | py36_0 624 KB conda-forge
tbb-2018_20171205 | 0 1.2 MB conda-forge
------------------------------------------------------------
Total: 31.8 MB

The following NEW packages will be INSTALLED:

boost: 1.64.0-py36_4 conda-forge
boost-cpp: 1.64.0-1 conda-forge
jemalloc: 5.1.0-hfc679d8_0 conda-forge
salmon: 0.10.2-1 bioconda
tbb: 2018_20171205-0 conda-forge

The following packages will be UPDATED:

conda: 4.5.4-py36_0 conda-forge --> 4.5.5-py36_0 conda-forge

Proceed ([y]/n)? y

Downloading and Extracting Packages
boost-1.64.0 | 331 KB | ####################################################################################################################################### | 100%
jemalloc-5.1.0 | 8.2 MB | ####################################################################################################################################### | 100%
boost-cpp-1.64.0 | 17.8 MB | ####################################################################################################################################### | 100%
salmon-0.10.2 | 3.7 MB | ####################################################################################################################################### | 100%
conda-4.5.5 | 624 KB | ####################################################################################################################################### | 100%
tbb-2018_20171205 | 1.2 MB | ####################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

RA at CSIR-URDIP

Fri, 10 Jul 2015 18:34:03 -0500

CSIR - UNIT FOR RESEARCH AND DEVELOPMENT OF INFORMATION PRODUCTS (CSIR- URDIP)

Adv. No. URDIP/ 15/2015

Opportunity for young Bioinformatics Professionals to make a career in the area of Intellectual Property

CSIR has set up a Unit for Research and Development of Information Products (CSIRURDIP) at Pune to work in the area of scientific informatics. One of the major focus areas of research work at CSIR-URDIP is PATENT INFORMATICS. With the increasing applications of Bioinformatics in the areas of life sciences industry such as Agriculture and Health Care (Diagnostics and Drugs), the output of research in these area is being protected by different forms of Intellectual Property rights. Realizing the importance of IP in the Bioinformatics field, Department of Biotechnology (DBT) has sanctioned a project on “Development, Facilitation and Harvesting of Bioinformatics related Intellectual Property” at CSIR-URDIP.

The project will involve application of Patent Informatics tools and techniques to Bioinformatics (including creation of patent landscapes, preparation of techno-legal reports of patentability, freedom to operate studies) to help protect IPRs and develop and conduct training programmes on IPRs related to Bioinformatics.

CSIR-URDIP invites applications from young Bioinformatics professionals to work on this emerging area which offers challenging opportunities and attractive career possibilities in future.

Position I: Research Associate

No of Positions: One

Consolidated amount Payable: = Rs 26,400.00

Qualification: PhD in Bioinformatics. In exceptional cases, candidature of M. Tech. candidates with First class in Bioinformatics with three years of relevant work experience will also be considered.

Job requirement: The prospective candidate will be expected to identify patents/scientific literature in field of Bioinformatics, evaluate them Vis a Vis other patents in fields and come up landscape / FTO / Patentability reports.

Age Limit: 35 years.

The candidates meeting the above criteria may appear for walk in interview at their cost on Monday 13th July 2015 at 02:00 p.m. with the CV and supporting documents (original plus copies) at the following address: CSIR Unit or Research and Development of Information Products (URDIP), "Tapovan" S.No. 113 & 114, Near NCL Colony Baner Side Gate, NCL Estate, Pashan Road, Pune-411008, Maharashtra, India

Advertisement: www.urdip.res.in/download/DBT_RA_Advt_July%202015.pdf

List of non-commercial NGS genotype-calling software

Jit — Thu, 09 Aug 2018 04:21:32 -0500

Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.

A list of programs for genotype and SNP calling :

SOAP2 http://soap.genomics.org.cn/index.html

Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)

realSFS http://128.32.118.212/thorfinn/realSFS/

Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation

Samtools http://samtools.sourceforge.net/

Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)

GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)

Beagle http://faculty.washington.edu/browning/beagle/beagle.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling

IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map

QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL

Multi-sample LD ‘Feasible’ genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The ‘feasible’ genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)

MaCH http://genome.sph.umich.edu/wiki/Thunder

Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information