• hist: Create an histogram of k-mer occurrences from a sequence file. Adds metadata in output for easy plotting.
• gcp: K-mer GC Processor. Creates a matrix of the number of K-mers found given a GC count and a K-mer count.
• comp: K-mer comparison tool. Creates a matrix of shared K-mers between two (or three) sequence files or hashes.
• sect: SEquence Coverage estimator Tool. Estimates the coverage of each sequence in a file using K-mers from another sequence file.
• blob: Given, reads and an assembly, calculates both the read and assembly K-mer coverage along with GC% for each sequence in the assembly.SEquence Coverage estimator Tool.
• filter: Filtering tools. Contains tools for filtering k-mer hashes and FastQ/A files:
  • kmer: Produces a k-mer hash containing only k-mers within specified coverage and GC tolerances.
  • seq: Filters a sequence file based on whether or not the sequences contain k-mers within a provided hash.
• plot: Plotting tools. Contains several plotting tools to visualise K-mer and compare distributions. The following plot tools are available:
  • density: Creates a density plot from a matrix created with the "comp" tool. Typically this is used to compare two K-mer hashes produced by different NGS reads.
  • profile: Creates a K-mer coverage plot for a single sequence. Takes in fasta coverage output coverage from the "sect" tool
  • spectra-cn: Creates a stacked histogram using a matrix created with the "comp" tool. Typically this is used to compare a jellyfish hash produced from a read set to a jellyfish hash produced from an assembly. The plot shows the amount of distinct K-mers absent, as well as the copy number variation present within the assembly.
  • spectra-hist: Creates a K-mer spectra plot for a set of K-mer histograms produced either by jellyfish-histo or kat-histo.
  • spectra-mx: Creates a K-mer spectra plot for a set of K-mer histograms that are derived from selected rows or columns in a matrix produced by the "comp".

In addition, KAT contains a python script for analysing the mathematical distributions present in the K-mer spectra in order to determine how much content is present in each peak.

This README only contains some brief details of how to install and use KAT. For more extensive documentation please visit: https://kat.readthedocs.org/en/latest/

https://academic.oup.com/bioinformatics/article/33/4/574/2664339 

Address of the bookmark: https://github.com/TGAC/KAT

More at https://attendee.gotowebinar.com/register/8452228815737989634

https://f1000research.com/articles/6-100/

https://github.com/jason-weirather/AlignQC

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/AlignQC/

Interested candidates may email their resume along with a cover letter to careers@arraygen.com

Official website: http://www.arraygen.com/

Address of the bookmark: https://github.com/clwgg/nQuireunder

New Delhi-110012

Walk in interview

Eligible candidates may appear for Walk-in interview for the temporary positions of JRF/SRF/ RA, in ICAR, DBT funded research projects. Positions are purely temporary in nature and are co-terminus with the projects. The initial appointment will be for maximum one year, which can be extended on the basis of assessment of the candidate performance and need in the project work (PI-Dr. N. K. Singh, National Professor).

Name of the

PI (Project)

Name of

Position

Number of

positions

Emoluments

Fixed per

month (Rs.)

Essential

Qualifications

DBT-“Physical Mapping and Sample sequencing of Wheat Chromosome 2A- International Wheat Genome Sequencing Consortium (India)”.

(Up to Nov,2014)

DBT- Identification and functional analysis of genes related to yield and biotic stresses (Up to Oct,2014)

NPTC-Central Facility

RA (Master)

JRF/SRF

Research Associate: One

Essential: MCA or M. Tech. (Bioinformatics and computer Science with 2 years experience in Database Management with

MySQL, Linux)

Desirable: Proficiency in handling of large biological databases

Age limit: Max. Age 35 years (Age of relaxation of 5 years for SC/ST& woman. and 3 years for OBC). The interview will be held on 08 July, 2014 at 11 am at room no. 39, NRCPB, LBS Building, Pusa Campus, New Delhi-110012. The candidates must bring original certificates and four copies of biodata, and recent passport size photograph. No TA/DA would be given for the appearance in interview. Only the candidates having essential qualifications would be entertained for the interviews.

Advertisement:

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Address of the bookmark: http://samstat.sourceforge.net/

Faculty of Science

Essential Qualifications:

(i) Good academic record having at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s Degree level in a relevant subject, from an Indian University, or an equivalent degree from an accredited foreign University.

(II) Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET.

(III) Notwithstanding anything contained in sub-clauses (i) and (ii) of clause 4.4.1 of UGC regulations 2010, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/ SLET/ SET for engagement of guest Teacher.

(IV) NET/ SLET/ SET shall also not be required for such Master’s Degree Programmes in discipline for which NET/ SLET/ SET is not conducted.

Application form along with detailed instructions can be downloaded from Tripura University website: www.tripurauniv.in. The duly filled in application forms complete in all respects may be sent so as to reach the Office of the Deputy Registrar Academic Branch, Tripura University, Suryamaninagar - 799022, Tripura on or before 31st July, 2014. The Candidates who responded against advertisement No. TU.REG/N-Advt./02/10 dated 20.02.2014 need not apply again.

For more info visit: http://www.tripurauniv.in/images/universitymedia/EmploymentNotification/Guest%20Teacher%20Advt.%20website_09072014.pdf

For more background see also the publication at BMC Bioinformatics.

https://github.com/clwgg/nQuire

Address of the bookmark: https://github.com/clwgg/nQuire

About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.

In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.

Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html