BOL: Related items

Structural polymorphism analysis from NGS data

Sat, 13 Jul 2013 17:12:47 -0500

The LabEx BASC (Biodiversity, Agroecosystems, Society, Climate), a network of 13 laboratories of the Paris-Saclay Scientific Cluster, is seeking a bioinformatician to analyze Next Generation Sequencing (NGS) data analysis. In the context of a flagship project aiming at understanding and improving the adaptive capacity of agroecosystems it will be critical to establish a link between sequence variation, functional variation, gene/protein expression and phenotypic adaptation.

The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).

The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development.

Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.

SNPGenie

Jit — Thu, 30 Mar 2017 17:38:02 -0500

SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a single population, with variants called relative to a single reference sequence (one sequence in one FASTA file). Just run the main script, snpgenie.pl, in a directory containing the necessary input files, and we take care of the rest! For the earlier version, see Hughes Lab Bioinformatics Resource.

Address of the bookmark: https://github.com/hugheslab/snpgenie

Dumontier Lab

Sun, 14 Jul 2013 12:51:42 -0500

Our research aims to better understand how living systems respond to chemical agents. A key aspect of our approach involves using computational frameworks that are powered by formal (i.e. machine understandable) semantics to make effectively use of vast and diverse amounts of biomedical knowledge. We are particularly interested in understanding how the response to chemical exposure is modulated by genetic and physiological variation among individuals and how this translates into altered capabilities at the molecular level.

Research Area

the discovery and on-demand use of biomedical data and services
the formulation, discovery and evaluation of scientific hypotheses
the simulation of biological systems at the level of individual molecules

Link @ http://dumontierlab.com/

NGS teaching material

Jit — Wed, 05 Apr 2017 04:29:06 -0500

High throughput sequencing (HTS) technologies are being applied to a wide range of important topics in biology. However, the analyses of non-model organisms, for which little previous sequence information is available, pose specific problems. This course addresses the specific strengths and weaknesses of alternative HTS technologies, the computational resources needed for HTS, and how to analyze non-model species using HTS. The course consists of a practical training module, HTS bioinformatics training, and lecturing/seminars of HTS approaches specifically targeting non-model organisms.

Address of the bookmark: http://marinetics.org/teaching/hts/Assembly.html

IBL laboratory

Mon, 12 Aug 2013 02:02:29 -0500

The IBL laboratory focuses on the multi-disciplinary analyses of the global responses of model microorganisms, cyanobacteria (mainly Synechocystis PCC6803) and yeasts (mainly Saccharomyces cerevisae) to environmental stresses triggered by oxidative agents, heavy metals, or drastic changes in nutrients availability. The genome-wide responses studied with the "omics" techniques (transcriptomics, proteomics, metabolomics and genetics) generate a wealth of experimental data, which are processed, archived, integrated and represented as working models through bioinformatics and mathematics.

Link : http://www-dsv.cea.fr/en/instituts/institut-de-biologie-et-de-technologies-de-saclay-ibitec-s/unites-de-recherche/service-de-biologie-integrative-et-genetique-moleculaire-sbigem/laboratoire-de-biologie-integrative-lbi/presentation__1

UpSetR Shiny App!

Jit — Fri, 14 Apr 2017 06:19:54 -0500

UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.

To begin, input your data using one of the three input styles.

"File" takes a correctly formatted.csv file.
"List" takes up to 6 different lists that contain unique elements, similar to that used in the web applications BioVenn (Hulsen et al., 2008) and jvenn (Bardou et al., 2014)
"Expression" takes the input used by the venneuler R package (Wilkinson, 2015)

Address of the bookmark: https://gehlenborglab.shinyapps.io/upsetr/

The Upton (VBRC) lab

Sun, 14 Jul 2013 13:25:41 -0500

This Bioinformatics Resource (Virology.ca, the Canadian half of the now defunct VBRC) focuses on large DNA viruses:
Poxviruses
African Swine Fever Viruses
Iridoviruses
Baculoviruses

Research Area

Custom searches of the viral databases
Building new tools .
The genome annotation

Link @ http://athena.bioc.uvic.ca/

RA Bioinformatics at JNU, New Delhi, INDIA

Thu, 27 Apr 2017 03:29:58 -0500

School of Computational & Integrative Sciences
Jawaharlal Nehru University
New Delhi-110067, INDIA

Date: April 24th. 2017 Last Date: May 6th 2017
PROJECT ID: 632

The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project jointly running with IIIT-Hyderabad & JNU, entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067.
NB: For all the posts, preference will be given to candidates with a good knowledge of Python and/or R in UNIX platform , knowledge of JAVA will also get a special consideration.

1. RA / Research Associate (Metabolic engineering/Computational Biologist)

Salary: Rs. 36000/- + HRA

Vacancy: 1

Essential Qualifications: PhD in Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/Analysis of Network Biology/Chemoinformatics/Computational Biology related Software development. Published paper in the field is a must to prove the experience. Special consideration will be given if have experience in Industry, teaching & product development.

Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , collaborating with industry , preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.

2. Project SRF (Network model building/Systems biology integration)

Salary*: Rs.18000/- + HRA

Vacancy: 1

Essential Qualifications: M.Tech in Computational Biology with project experience or Masters / B.Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Mathematical Model building using Computational Biology tools & related Database / Network analysis etc. For M.Sc/B.Tech, Published paper in peer-reviewed Journal whereas for M.Tech, the degree obtained in computational biology is a must.

Desired Skills: Will be expected to manage ongoing research activities in LIMS, interact with LIMS group, build network model using data compiled by experimentalist, prepare and file reports and associated project work etc. Familiarity with plant systems biology and genomics /metabolite resources related to plant metabolomics is desirable.

More at http://www.jnu.ac.in/Career/currentjobs.htm

Welch Lab

Mon, 15 Jul 2013 18:21:13 -0500

They are based in the Department of Genetics at the University of Cambridge.

The research covers diverse areas of evolutionary biology, and molecular evolution in particular. It combines theoretical and empirical approaches, and particularly evolutionary inference from genome sequence data.

Links @ http://www.gen.cam.ac.uk/research/welch/GroupPage/Home.html

Mapping NGS

Abhimanyu Singh — Tue, 02 May 2017 07:58:07 -0500

NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...
To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.
In either way, aligning your sequence reads to the reference sequence is called mapping.

The most used mappers of DNA-seq data are BWA and Bowtie for DNA-Seq data and Tophat, STAR or HISAT for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).

Address of the bookmark: http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data