BOL: Related items

Google Genomics

Reshma Khatun — Fri, 17 Oct 2014 02:14:14 -0500

Google Genomics provides an API to store, process, explore, and share DNA sequence reads, reference-based alignments, and variant calls, using Google's cloud infrastructure.

Store alignments and variant calls for one genome or a million.
Process genomic data in batch by running principal component analysis or Hardy-Weinberg equilibrium, in minutes or hours, by using parallel computing frameworks like MapReduce.
Explore data by slicing alignments and variants by genomic range across one or multiple samples -- for your own algorithms or for visualization; or interactively process entire cohorts to find transition/transversion ratios, allelic frequency, genome-wide association and more using BigQuery.
Share genomic data with your research group, collaborators, the broader community, or the public. You decide.

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/

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

Research Scientist – National Institute of Cholera and Enteric Diseases

Wed, 22 Oct 2014 10:26:46 -0500

The following post is to be filled up on purely temporary basis under the project entitled "Second phase of Task Force Biomedical Informatics Center of ICMR" under Dr. Santasabuj Das, Scientist 'D' of this Institute:-

01. Scientist II 01
Essential: Ph.D. degree in Life Sciences from a recognized university along with a minimum of 2 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

OR
Ph.D. degree in Bioinformatics from a recognized university.

OR
M.Sc. in Bioinformatics from a recognized university along with a minimum of 3 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

Desirable:
Thorough Knowledge about In silico genome analysis and comparative genomics.
Experience with in silico identification of novel virulence factors of pathogens, host-pathogen interactions and Systems Biology.
Additional Postdoctoral research experience in relevant subjects from a recognized institutions.

Rs. 44,000/- p.m. (consolidated) plus 30% HRA

Below 40 years

Applications along with Bio-Data containing detail work experience and full list of publications may be sent via email tosantasabujdas@yahoo.com latest by October 27, 2014.

Short-listed candidates will be called via email for an interview to be held at the institute in the second week of November, 2014.

Advertisement: www.niced.org.in/placements.htm

RNA-seq Analysis Workshop Course Materials

Jit — Tue, 03 Jul 2018 08:14:14 -0500

RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves our ability to reconstruct transcripts. This category would obviously include humans and most model organisms but excludes the majority of truly biologically intereting species (e.g., Hyacinth macaw); Reference genome-free - no genome assembly for the species of interest is available. In this case one would need to assemble the reads into transcripts using de novo approaches. This type of RNAseq is as much of an art as well as science because assembly is heavily parameter-dependent and difficult to do well. In this lesson we will focus on the Reference genome-based type of RNA seq. http://chagall.med.cornell.edu/RNASEQcourse/

Address of the bookmark: http://chagall.med.cornell.edu/RNASEQcourse/

Celebrating Crystallography - An animated adventure

Fri, 31 Oct 2014 15:59:00 -0500

NEW: Now with French or Spanish subtitles (click on the 'Captions' icon to select). Plus... Watch the French language version here: https://www.youtube.com/watch?v=PvLu7BOsJhM X-ray crystallography is arguably one of the greatest innovations of the twentieth century, but not that many people know what it is or how it came about. Join us on an animated journey through the 100 year history of crystallography -- from the pioneering work of William and Lawrence Bragg in 1913 to the surface of Mars! Narrated by structural biologist Stephen Curry and produced by animation company 12foot6, the film explores the extraordinary history of crystallography. To date 28 Nobel Prizes have been awarded to projects related to the field and X-ray crystallography remains the foremost technique in determining the structures of a huge range of complex molecules. This film was produced in celebration of the Bragg Centenary and was funded by STFC. Watch more science videos on the amazing Ri Channel: http://richannel.org Watch more animations from 12foot6: http://12foot6.com/ The Ri is on Twitter: http://twitter.com/ri_science and Facebook: http://www.facebook.com/royalinstitution Subscribe for the latest science videos: http://richannel.org/newsletter

AlignQC: A tool for assessing an alignment, and generating reports that are easy to share

Jit — Tue, 07 Aug 2018 04:41:07 -0500

Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.

https://f1000research.com/articles/6-100/

https://github.com/jason-weirather/AlignQC

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/AlignQC/

Postdoctoral fellowship in Bioinformatics

Sat, 08 Nov 2014 14:41:14 -0600

A two-year post-doctoral position is available in the Biocomputing group of the Sapienza University led by Anna Tramontano to work on either genomics research or structural bioinformatics, focusing on the study of relevant biomedical problems.
The ideal candidate should be motivated and talented, hold a PhD degree, have good programming skills, a grasp of statistical methods and an understanding of biology.
Experience in the development of computational biology methods would be an added value.

Good communication skills and fluency in spoken and written English are required.
Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”

Deadline: No later than November 28th, 2014.
Duration: 2 years

Salary on grant: Commeasured to the experience of the candidate
Contact Person (Referent): Anna Tramontano
Ref. E-Mail: anna.tramontano@uniroma1.it
Group Web Page: http:/www.biocomputing.it

Platypus: A Haplotype-Based Variant Caller For Next Generation Sequence Data

Shruti Paniwala — Thu, 25 Oct 2018 06:14:55 -0500

Platypus is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect SNPs, MNPs, short indels, replacements and (using the assembly option) deletions up to several kb. It has been extensively tested on whole-genome, exon-capture, and targeted capture data, it has been run on very large datasets as part of the Thousand Genomes and WGS500 projects, and is being used in clinical sequencing trials in the Mainstreaming Cancer Genetics programme.

Tutorial https://github.com/andyrimmer/Platypus/blob/master/misc/README.txt

Address of the bookmark: http://www.well.ox.ac.uk/platypus

Centre for Systems Biology & Bioinformatics, Panjab University vacancy of Research Fellow

Wed, 12 Nov 2014 06:18:54 -0600

Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of
Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology & Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of the project

Essential Qualification
For Research Fellow:-
M.Sc. in Systems Biology and Bioinformatics / Life
Sciences with minimum 55% marks.
Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf

snakepipes: A toolkit based on snakemake and python for analysis of NGS data

Jit — Thu, 30 May 2019 04:06:13 -0500

snakePipes are flexible and powerful workflows built using snakemake that simplify the analysis of NGS data.

DNA-mapping*
ChIP-seq*
RNA-seq*
ATAC-seq*
scRNA-seq
Hi-C
Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes