BOL: Related items

Nataša Pržulj Lab

Fri, 30 Aug 2013 06:29:17 -0500

Nataša Pržulj Lab's research involves applications of graph theory, mathematical modeling, and computational techniques to solving large-scale problems in computational and systems biology.They are interested in computational and theoretical solutions to practical problems in many areas of systems biology, planar cell polarity, proteomics, cancer informatics, and drug discovery and design.

More at http://www.doc.ic.ac.uk/~natasha/index.html

RA Bioinformatics at NII

Thu, 22 Oct 2015 01:56:26 -0500

NATIONAL INSTITUTE OF IMMUNOLOGY

NEW DELHI-110067

Applications are invited for the position of Research Associate (RA) for the following time-bound sponsored project as per the details given below:

1. BTIS project entitled, “National Infrastructural Facility in the Area of Immunology” funded by DBT

Research Associate (One Position only)

Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in

Educational Qualifications: Ph.D in Bioinformatics or Biological Sciences or Biotechnology with research experience and publication record in indexed peer reviewed journals in the area of bioinformatics or computational biology.

Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications & experience Research Associate: Rs. 36,000/- per month plus 30% HRA

Job description & Desired Knowledge: The candidate should be well versed in Programming in PERL/C++, HTML, CGI, web sever and portal development, computational analysis of protein structure & function, molecular dynamics simulations and use of high performance computing systems.

General Terms & Conditions:-

1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.

2. No hostel/ housing facility will be provided.

3. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.

4. No TA/DA will be paid for attending the interview, if called for.

5. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise and list of publications. 6. Canvassing in any form will be a disqualification.

HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., Email ID, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC/ST/PH and Women candidates are exempted from payment of fees) subject to submission of documentary proof), at the time of interview. (E-MAIL APPLICATIONS SHOULD MENTION BTIS-RA 2015 IN THE SUBJECT LINE)

LAST DATE OF RECEIPT OF APPLICATIONS: 29th October, 2015

www1.nii.res.in/sites/default/files/projectappointments-Dr.Mohanty-29oct2015.pdf

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/

Scripts for the analysis of HGT in genome sequence data.

Jit — Wed, 29 Nov 2017 16:44:10 -0600

Scripts for the analysis of HGT in genome sequence data

Address of the bookmark: https://github.com/reubwn/hgt

Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data

Jit — Thu, 19 Apr 2018 08:06:03 -0500

Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from https://github.com/meiji-bioinf/heap and our web site (http://bioinf.mind.meiji.ac.jp/lab/en/tools.html).

Address of the bookmark: https://github.com/meiji-bioinf/heap

Epiviz: an interactive visualization tool for functional genomics data.

Jit — Mon, 09 Jul 2018 05:27:39 -0500

Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations. It also includes data from the Gene Expression Barcode project for transcriptome visualization. It has a flexible plugin framework so users can addd3 visualizations. You can see a video tour here.

https://bioconductor.org/packages/release/bioc/html/epivizr.html

https://github.com/epiviz

https://github.com/epiviz/epiviz

Address of the bookmark: https://epiviz.github.io/

VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules

Rahul Nayak — Thu, 04 Oct 2018 16:30:44 -0500

VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.

Address of the bookmark: https://github.com/broadinstitute/VariantBam

EXCAVATOR: detecting copy number variants from whole-exome sequencing data

Radha Agarkar — Fri, 04 Jan 2019 10:10:48 -0600

EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.

EXCAVATOR is a novel software package for the detection of copy number variants (CNVs) from whole-exome sequencing data.
EXCAVATOR has been published on Genome Biology (http://genomebiology.com/2013/14/10/R120/abstract).

Address of the bookmark: https://sourceforge.net/projects/excavatortool/

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

Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.

Jit — Tue, 21 Jan 2020 04:22:49 -0600

Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the DeltaRho environment.

For those familiar with Trellis Display, faceting in ggplot, or the notion of small multiples, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.

Address of the bookmark: http://deltarho.org/docs-trelliscope/#introduction