BOL: Related items

gVolante: Completeness Assessment of Genome/Transcriptome Sequences

Jit — Tue, 06 Aug 2019 21:37:56 -0500

gVolante provides an online interface for completeness assessment of user’s original or publicly available sequence datasets as well as for browsing results of completeness assessment performed on publicly available genome and transcriptome assemblies.

Address of the bookmark: https://gvolante.riken.jp/

Senior Research Fellow at NIT, Rourkela

Wed, 30 Jul 2014 00:53:13 -0500

NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA – 769 008(ORISSA)
SPONSORED RESEARCH, INDUSTRIAL CONSULTANCY & CONTINUING EDUCATION

ADVERTISEMENT NO: NITR/SR/CH-BIF/2014/30

Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Biotechnology & Medical Engineering of the Institute.

1. Name of the Temporary Post : Senior Research Fellow-01
2. Name of the Research Project: “ Bioinformatics Infrastructure Facility (BIF)”
3. Name of the Sponsoring Agency: DBT, Government of India, 4 Tenure of the Project : 12th Five year Plan
5 Tenure of the Assignment : 01 year [Likely to be extended for 04 more years]
6 Job Description : BIF Maintenance and Active Research in Bioinformatics
7. Consolidated monthly compensation / Fellowship: Rs.18,000/- P.M.

8. Essential Qualifications and experience: B.Tech with valid GATE Score or M.Tech degree in Biotechnology/Bioinformatics/Computer Science/Computational Biology
9. Desirable Qualifications/ Experiences: Experience of Programming in PERL,R, Python, Unix and Visual Studio + Knowledge in NGS data analysis work flows ,WGS and statistical packages such as CRAN-R,MATLAB etc.

10. Accommodation : Bachelor accommodation in the Institute may be provided subject to availability.
11. For technical information on the project, the candidate may contact the Principal Investigator at the following address:

Name : Prof. Mukesh K Gupta
Address : Dept. of Biotechnology & Medical Engineering,
N.I.T.Rourkela-769 008
Telephone No : 0661-2462294
E-mail : guptam@nitrkl.ac.in

Eligible persons may apply in the prescribed format (available in the Institute Website)affixed with coloured photographs to be submitted in duplicate along with photo copies of relevant certificates, grade/ mark sheets, publications etc., to Asst. Registrar, SRICCE,
National Institute of Technology, Rourkela–769 008 before 22.08.2014. The cover should be super- scribed clearly the post applied for & Name of the Project.

Mere possession of minimum qualification does not guarantee invitation to the interview.
Candidates will be short listed based on merit and need of the project.

http://www.nitrkl.ac.in/IntraWeb/Jobs_Tenders/Jobs/ProjectFellowship/2014/141707192838_1.pdf

Genome Informatics Section Lab !

Sat, 25 Jan 2020 06:38:23 -0600

Our section develops and applies computational methods for the analysis of massive genomics datasets, focusing on the challenges of genome sequencing and comparative genomics. We aim to improve such foundational processes and translate emerging genomic technologies into practice.

The Genome Informatics Section is hiring! Come join our outstanding team at the NIH’s National Human Genome Research Institute and contribute to the development of new reference genomes and computational methods for DNA sequencing and analysis. Both postdoc and PhD students positions are available. More information and application instructions follow below.

More at https://genomeinformatics.github.io/

MEGADOCK 4.0

Suleman Khan — Thu, 07 Aug 2014 18:08:54 -0500

An ultra–high-performance protein–protein docking software for heterogeneous supercomputers

Summary: The application of protein–protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.

Availability and Implementation: MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock.

Contact: akiyama@cs.titech.ac.jp

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

Neel — Sun, 20 Dec 2020 01:39:54 -0600

The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads. Described by Alser et al. (preliminary version at https://arxiv.org/abs/1910.09020).

Address of the bookmark: https://github.com/CMU-SAFARI/SneakySnake

GrapheR !!!

John Parker — Thu, 14 Aug 2014 14:02:17 -0500

What a wonderful gem GrapheR is.... Oh yes it is. GrapheR is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console.

Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.
Here is a little example using the iris data set.

library(GrapheR)
data(iris)
run.GrapheR()

This will bring up a window that helps me to create the chart and tweak the various parameters.

Finally, I find the underlying R code in a file created by GrapheR. For more details read also the package vignette, which is available in English, French and German!

Simons Genome Diversity Project

Jit — Sat, 08 May 2021 21:55:25 -0500

Complete genome sequences from more than one hundred diverse human populations

All genomes in the dataset were sequenced to at least 30x coverage using Illumina technology. The sequencing reads were mapped and genotyped using a customized procedure that was optimized for population genetic analysis. The researchers eliminated bias of alleles toward matching the human genome reference sequence, and determined genotypes on a single-sample basis to avoid preferential calling of genotypes from populations that had more individuals represented.

Address of the bookmark: https://www.simonsfoundation.org/simons-genome-diversity-project/

pybedtools

Shruti Paniwala — Wed, 20 Aug 2014 01:03:41 -0500

pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.

More at http://pythonhosted.org/pybedtools/

A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/

HISAT2 Index Files Download !

LEGE — Wed, 15 Sep 2021 22:17:49 -0500

Resource for downloading all the HISAT2 related files

Please cite:

Kim, D., Paggi, J.M., Park, C. et al. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 37, 907–915 (2019). https://doi.org/10.1038/s41587-019-0201-4

Address of the bookmark: http://daehwankimlab.github.io/hisat2/download/#h-sapiens

UniqueKmer: Generate unique KMERs for every contig in a FASTA file

Abhi — Fri, 17 Dec 2021 00:08:15 -0600

Generate unique k-mers for every contig in a FASTA file.

Unique k-mer is consisted of k-mer keys (i.e. ATCGATCCTTAAGG) that are only presented in one contig, but not presented in any other contigs (for both forward and reverse strands).

This tool accepts the input of a FASTA file consisting of many contigs, and extract unique k-mers for each contig.

The output unique k-mer file and Genome file can be used for fastv: https://github.com/OpenGene/fastv, which is an ultra-fast tool to identify and visualize microbial sequences from sequencing data.

https://github.com/OpenGene/UniqueKMER

Address of the bookmark: https://github.com/OpenGene/UniqueKMER