We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on “unusual” sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set.

When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain.

Availability: The method is publicly available athttp://research.haifa.ac.il/~ssagi/software/nearHGT.zip

Address of the bookmark: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004408

For the full list of features, improvements and fixes, see the release notes:https://ncbi.nlm.nih.gov/tools/gbench/releasenotes

New Features

• BLAST Tool: added support for local custom BLAST databases
• Graphical Sequence View: added log scaling option for graph tracks
• Generic Table View: new tutorial added

Bug Fixes and Improvements

• Project Tree View: Genomic Collections/Assemblies now show accessions, not just names
• Tree View: layout updated to better accommodate nodes of different sizes
• Table Import Dialog (MacOS): fixed issue with table visibility
• Fixed bug where different molecules IDs in GenBank could resolve to the same sequence
• Graphical Sequence View: fixed issue where sequence track was not shown for some sequences
• Graphical Sequence View: fixed protein coloration methods
• Graphical Sequence View: improved rendering of Markers to better indicate boundaries and produce higher quality PDF images
• Create Gene Model tool: fixed scenario when gene model tool failed with local sequences
• Search View: ORF Finder – fixed incorrect protein lengths
• Fixed bug with not opening project file (.gbp) on a click
• Fixed issues in GVF import
• Fixed BLAST Search tool against NCBI databases not working
• Fixed tblastn (protein BLAST) not working in standalone mode
• Fixed GTF export failure

Applications are invited for a post in DST, India funded Project entitled: "Positive and negative impacts of macromolecular crowding agents during target site location by DNA binding proteins – origin of optimal search at physiological ionic concentration (Reference Number: ECR/2016/000188) ''. The selected candidate will be appointed purely on temporary basis, initially for two years as a JRF that may be extended to one year of SRF based on the performance.

Position: Junior Research Fellow (1)

Qualifications & Experience: Candidate must have a consistently good academic record with at least 60% marks in all throughout and must have qualified NET/GATE.

Desirable: Basic knowledge in the field of biophysics, molecular simulations and computational biology are desirable.

Salary: Consolidated Rs. 25,000 per month.

Tenure: The project duration is for three years and the selected candidate would be appointed after an interview. Appointment will be purely on temporary basis as stipulated by the existing rules of the University.

Interested candidates need to send an application to the address mentioned below mentioning the name of the project and post applied for (on the cover of the envelope).

The applications along with CV should be mailed at the address given below. Name, address, contact number and e. mail address of two referees must be enclosed with the application. The last date for the application is July 31st 2016.

Dr. Arnab Bhattacharjee (Principal Investigator)
Assistant Professor
School of Computational and Integrative Sciences
Jawaharlal Nehru University
New Delhi-110067
E-mail: arnab@jnu.ac.in

Note: 1. Only shortlisted candidates will be communicated to appear in the interview at SCIS, JNU and no other communications in this regard will be entertained.

2. No TA/DA will be paid for appearing in interview.

More at http://ird.iitd.ac.in/sites/default/files/jobs/project/IITD-IRD-093-2016.pdf

EMBASSY applications are described in separate documentation for each package.

Applications in the current release

Address of the bookmark: http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/

Fellowship: Rs. 18,000/- per month (fixed)

Duration : 2 (Two) years and may be extended
depending on status of the project

Age Limit: Candidates should not be more than 32 years of
age in case of SRF and 28 years of age in case of JRF and TA. Upper age limit may be relaxed up to 5
years in the case of candidate belonging to SC/ ST/ OBC/ Women/ Differently abled.

How to Apply:
Interested candidates may send their application on plain paper by post along with his/her educational
qualifications, research experience certificates (for SRF), 02 copies of recent passport/stamp size photographs
and contact phone number to Professor D.K Bhattacharyya, Principal Investigator, Department of Computer
Science & Engineering, Tezpur University, Napaam – 784 028, or mail it to dkb@tezu.ernet.in
(or to smh@tezu.ernet.in) within 15 days of publication of this advertisement.

No TA/DA shall
be paid for attending the interview.

For more details: http://www.tezu.ernet.in/ProjectWalkin/Advt-DoRD-CSE-DKB-20-225-6779-A.pdf

Address of the bookmark: http://omega.omicsbio.org/

a) Scientist-B – UR (2 posts-Bioinformatics) on consolidated salary of Rs.48,000/- pm + HRA

b) Scientist C – UR (1 post -Bioinformatics) on consolidated salary of Rs. 51,000 pm+ HRA

c) Scientist B- UR (2 post-Statistics) on a consolidated salary of Rs.48,000/- pm +HRA

d) Computer Programmer 1 post UR & 1 post SC on a consolidated salary of Rs. 32,500/- pm

e) Research Assistant -UR 1 post on a consolidated salary of Rs. 31,000/- pm

More at https://projectjobs.icmr.org.in/sccbioinformatics/uploads/recruitment/Adv_BMI_24122020.pdf

So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are PacBio E. coli sample, ERS473430, ERS544009, ERS554120, ERS605484, ERS617393, ERS646601, ERS659581, ERS670327, ERS685285, ERS743109 and a deprecated PacBio E. coli data set. ONT data are acquired from the Loman Lab.

For a C. elegans PacBio data set (only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the HGAP3produces a 104Mb assembly with N50 1.61Mb. This dotter plot gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.

Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that minimap can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as MHAP and DALIGNER. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.

Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)

We start with an all against all comparison:

minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 > reads.paf.gz

Then we can assemble

miniasm -f reads.fq reads.paf.gz > reads.gfa

Convert GFA to FASTA:

awk '/^S/{print ">"$2"\n"$3}' reads.gfa | fold > reads.fa

And then count how many contigs:

grep ">" reads.fa | wc -l

# Download sample PacBio from the PBcR website
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz | tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
# Install minimap and miniasm (requiring gcc and zlib)
git clone https://github.com/lh3/minimap && (cd minimap && make)
git clone https://github.com/lh3/miniasm && (cd miniasm && make)
# Overlap
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 > reads.paf.gz
# Layout
miniasm/miniasm -f reads.fq reads.paf.gz > reads.gfa

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

Address of the bookmark: https://github.com/marbl/MashMap