BOL: Related items

Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra

Tue, 30 Aug 2016 04:16:15 -0500

Scientist
Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra
Scientist (One position)
Project: Bioinformatics centre DBT- Sub-DIC at ACTREC
Funding agency: DBT Grant No.232

Duration of the Project: Six Months from the date of appointment can be extended further for six months
Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&D experience in Bioinformatics or relevant subjects from recognized institutes.
OR
Ph.D. degree in Bioinformatics or Life Sciences from recognized University.
M.Sc. degree obtained after a one year course will not be considered.
Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s).

More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx

Genome assembly stats plotting

Jit — Wed, 28 Feb 2018 03:45:39 -0600

A de novo genome assembly can be summarised b

y a number of metrics, including:

Overall assembly length
Number of scaffolds/contigs
Length of longest scaffold/contig
Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns
CEGMA completeness
Scaffold/contig length/count distribution

assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.

Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.

Address of the bookmark: https://github.com/rjchallis/assembly-stats

R-chie

Jit — Thu, 01 Sep 2016 11:47:24 -0500

R-chie allows you to make arc diagrams of RNA secondary structures, allowing for easy comparison and overlap of two structures, rank and display basepairs in colour and to also visualize corresponding multiple sequence alignments and co-variation information.
R4RNA is the R package powering R-chie, available for download and local use for more customized figures and scripting.

http://www.e-rna.org/r-chie/plot.cgi?eg=single

Address of the bookmark: http://www.e-rna.org/r-chie/plot.cgi?eg=single

HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies

Jit — Tue, 15 May 2018 07:35:26 -0500

HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to: NGS short reads (Illumina HiSeq) clone-based sequencing (Fosmid or BAC clones) SMRT reads (PacBio) Oxford Nanopore reads 10X Genomics Linked-Reads proximity-ligation (Hi-C) reads high-coverage sequencing (>40x coverage-per-SNP) using above technologies combinations of the above technologies (e.g. scaffold long reads with Hi-C reads) See below for specific examples of command line options and best practices for some of these technologies. NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants. If you use HapCUT2 in your research, please cite: Edge, P., Bafna, V. & Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116

Address of the bookmark: https://github.com/vibansal/HapCUT2

Assembly tutorial PPT

Jit — Wed, 07 Sep 2016 03:12:53 -0500

Saved Cornell University assembly workshop PPT.

Reference:

http://cbsu.tc.cornell.edu/lab/doc/assembly_workshop_20150420_lecture1.pdf

SWALO: Scaffolding with assembly likelihood optimization

Jit — Wed, 20 Jun 2018 02:45:16 -0500

SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing. Please email your questions, comments, suggestions, and bug reports to atif.bd@gmail.com.

Address of the bookmark: https://atifrahman.github.io/SWALO/

FERMI

Jit — Fri, 09 Sep 2016 05:37:13 -0500

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of
unitigs to represent all the information in raw reads.

Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index (FMD-index) as the key data structure. It is inspired by the string graph assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.

As a typical de novo assembler, fermi tends to produce contigs with slightly longer N50. However, the major weakness of fermi is the high misassembly rate. Although fermi provides a tool to fix misassemblies by using paired-end reads to achieve an accuracy comparable to other assemblers, this is not a favorable solution.

Fermi is designed to be used on a multi-core Linux machine with large shared memory. The easiest way to run fermi is to use the run-fermi.pl script. It generates a Makefile. The actual assembly is done by invoking make. Premature assembly processes can be resumed. Here is an example:

run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz > NA12878.mak
make -f NA12878.mak -j16

Address of the bookmark: https://github.com/lh3/fermi

Converting a VCF into a FASTA given some reference !

Jit — Fri, 20 Jul 2018 10:03:53 -0500

Samtools/BCFtools (Heng Li) provides a Perl script vcfutils.pl which does this, the function vcf2fq (lines 469-528)

This script has been modified by others to convert InDels as well, e.g. this by David Eccles

./vcf2fq.pl -f <input.fasta> <all-site.vcf> > <output.fastq>

https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl

https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl

SRF Bioinformatics at Bose Institute, India

Thu, 29 Sep 2016 09:39:13 -0500

Advt. No. S/DPB(CB)/17/2016-17
Junior Research Assistant/ Senior Research Assistant Job vacancies in Bose Institute on temporary basis
Project Title : “Genome wide transcriptome analysis to identity MYMIV-stress related genomic resources of blackgram”
Junior Research Assistant
Qualification : Good academic record in B.Sc. and M.Sc. in Botany or Biotechnology from reputed Universities. Must have good practical hand, this should be certified by two Senior/reputed PG teachers on a scale of 10.
Desirable : Preference will be given to those who already have some research experience (for at least 2 months).
Consolidated Pay : Rs. 16,400/- p.m.
Age Limit : Below 28 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).
Senior Research Assistant
Qualification : B.Sc. in Biotechnology and M.Sc. in Biotechnology or Bioinformatics. Hands on training in Bioinformatics. At least two Research Publications with Bioinformatics components.
Desirable : Preference will be given to the candidates who have previous experience in Next Gen Sequencing data analysis of genomic/transcriptome/miRNA.
Consolidated Pay : Rs. 18,700/- p.m.
Age Limit : Below 30 years (relaxable in case of SC/ST/OBC/Women candidates only as per rules).

http://www.boseinst.ernet.in/advertisement.html

Long read assembly workshop !

Rahul Nayak — Thu, 04 Oct 2018 17:23:18 -0500

This is a tutorial for a workshop on long-read (PacBio) genome assembly.

It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.

Please comment if you know any other long read addembly tutorial.

Address of the bookmark: http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/