Of course, some long read correction algorithms are better than others, and developers of long read correction algorithms will wish to compare their algorithm with others currently available. LRCstats benchmarks long read correction algorithms using long reads produced by simulators (such as SimLoRD or PBSim) where the two-way alignments between the uncorrected long reads (uLR) and the corresponding sequences in the reference genome (Ref) are given in some sort of alignment file and then aligning the corrected long reads (cLR) to the Ref-uLR two-way alignments to create three-way alignments using a dynamic programming algorithm. Statistics on these three-way alignments are then collected, such as the overall error rates of the corrected long reads.

https://www.healthcare.uiowa.edu/labs/au/LSC/

Address of the bookmark: https://github.com/cchauve/lrcstats

GARGI COLLEGE (University of Delhi)

SiriFort Road, New Delhi-110049

Walk- in- interview Bioinformatics Infrastructure Facility (BIF), Gargi College, University of Delhi invites to appear for interview on 29th September, 2015 at 9.30 AM for filling up the following purely temporary position sponsored by DBT, New Delhi.

1. Traineeship – 01 (one post) purely temporary for a period of six months.

Salary: Rs.8000/- p.m. fixed.

Essential Qualification: Post Graduate degree in Bioinformatics or any other branch of Life Sciences preferably with dissertation in Bioinformatics.

Desirable Qualification: Prior knowledge of programming languages such as C, VB, SQL etc. and software/database development.

2. Research Associate-01(one post) purely temporary for a period of nine months.

Salary: Rs 36000/-+HRA p.m fixed.

Essential Qualification: PhD in Bioinformatics/Biological Sciences/Computer Science or allied sciences with proven experience in bioinformatics.

3. Studentship- 01 (one post) purely temporary for a period of six months.

Salary: Rs.8000/- p.m. fixed.

Essential Qualifications: Final year Post Graduate students pursuing a degree in Bioinformatics or any branch of Life Science with knowledge of bioinformatics.

Interested candidates are required to appear for the walk in interview on 29th September, 2015 at 9.30 AM in Principal’s Office, Gargi College, Sirifort Road, N. Delhi-110049, with their CVs, original documents and a set of Photostat copies of all original documents. Conditions: The original documents must be produced at the time of interview, otherwise will not be allowed to attend the same. No TA & DA will be paid for appearing in the interview. The institute reserves the right to fill or not to fill the positions depending upon qualifications/credentials of the candidates etc. The appointment does not confer any right over the job and will not be considered as institute’s service. Dr Aparajita Mohanty Dr Shashi Tyagi (Co-coordinator,BIF) (Coordinator, BIF)

Advertisement:

http://gargi.du.ac.in/uploads/ngrey/News/Gargi_Advt_BIF_2015.pdf

Address of the bookmark: https://github.com/dfguan/rHAT

Name of post: Research Associate
Salary: Rs.36000/-+ 30% HRA*
Educational Qualification: Candidates should have PhD in Biotechnology / Bioinformatics Life Sciences (or) M.Sc Biotechnology / Bioinformatics with three years research experience in relevant field

Name of post: Junior Research Fellow
Salary: Rs.25000/-+ 30% HRA*
Educational Qualification: Candidates should have M.Sc in Biotechnology /Bioinformatics / Life Sciences with 1st Division or 60% marks or equivalent overall grade point from any recognized professional University

Age Limit: 35 years max. (5 years relaxation for SC/ST/OBC)

How to attend walk in interview?
Interested candidates may attend Walk- in-interview on 1st October, 2015 at 10 am at NRCPB, LBS Building, Pusa Campus, and New Delhi-110012 at the above address along with updated Bio-data (CV), ID Proof & attested copies of Certificates and Original to prove qualification & Experience.

Recruitment reference: http://www.nrcpb.org/jobslist

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

Detail paper at https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8

Address of the bookmark: https://github.com/VicugnaPacos/ALPACA

(A Central University established by an Act of Parliament)

Prof. C.R.Rao Road, P.O. Central University Campus, Gachibowli,

Hyderabad - 500 046

Advt.No. UH/HR/Rectt-2015/02 dt. 12.10.2015

The University invites applications from the Indian citizens for the following positions:

Professor / Associate Professor / Assistant Professor :

Biotechnology & Bioinformatics

Last date : 16th November 2015

More Info : http://www.uohyd.ac.in/images/recruitment/advt-121015.pdf

Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The “target.fasta.sa” is the suffix array from “target.fasta” generated by sawriter.

blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15

the output format option “-m 4″ generate the alignment coordinate. Not fully documented, but I can explain that to you. 

I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.

Address of the bookmark: http://bix.ucsd.edu/projects/blasr/

JRF /1

Qualification : Master’s Degree in Biotechnology / life sciences with four years Bachelor’s Degree (or) Master’s Degree in Biotechnology / life sciences with NET qualification with 1st Division or 60% marks or equivalent overall grade point average . Non NET/ Master’s degree with three years Bachelor’s degree as per DST/DBT norms. Desirable: Working Experience in Molecular Biology Techniques, genome sequence analysis Bioinformatics

Emoluments : Rs.25000

SRF

Qualification : Master’s degree in Biotechnology/Bioinformatics/Life Science with 1st division or 60% marks or equivalent overall grade point average with 4 year of Bachelor’s degree or 5 years integrated Masters degree. Desirable: Working experience in Bioinformatics, genomic analysis

Emoluments : Rs.25000/

Age Limit: 35 years

Walk-in-interview will be held on 20th November 2015 at 10 AM at NRCPB, LBS Building, Pusa Campus, and New Delhi-110012

More at http://www.nrcpb.org/sites/default/files/Adverdisement_0.pdf