• Filters SNVs from any variant caller to remove false positives
• Calculates metrics based on BAM files and provides filtering not possible with other tools
• Fully user-configurable filtering (including which filters to use and their thresholds)
• Option to use filters identical to ICGC recommendations

FiNGS provides researchers with a tool to reproducibly filter somatic variants that is simple to both deploy and use, with filters and thresholds that are fully configurable by the user. It ingests and emits standard variant call format (VCF) files and will slot into existing sequencing pipelines. It allows users to develop and implement their own filtering strategies and simple sharing of these with others.

FiNGS reliably improves upon the precision of default variant caller outputs and performs better than other tools designed for the same task.

Address of the bookmark: https://github.com/cpwardell/FiNGS

In our day to day research activity, we need to securely copy our data from several to local computer and visa-versa. I am jotting down some of the commonly used SCP command for your future help. Hope you all will like it

What is Secure Copy?

scp allows files to be copied to, from, or between different hosts. It uses ssh for data transfer and provides the same authentication and same level of security as ssh.

Examples

Copy the file "gene.txt" from a remote host to the local host

    $ scp your_username@remotehost.edu:gene.txt /some/local/directory

Copy the file "foobar.txt" from the local host to a remote host

    $ scp gene.txt your_username@remotehost.edu:/some/remote/directory

Copy the directory "chromosome" from the local host to a remote host's directory "bar"

    $ scp -r chromosome your_username@remotehost.edu:/some/remote/directory/bar

Copy the file "gene.txt" from remote host "rh1.edu" to remote host "rh2.edu"

    $ scp your_username@rh1.edu:/some/remote/directory/gene.txt \
    your_username@rh2.edu:/some/remote/directory/

Copying the files "gene.txt" and "cancer.txt" from the local host to your home directory on the remote host

    $ scp gene.txt cancer.txt your_username@remotehost.edu:~

Copy the file "gene.txt" from the local host to a remote host using port 2264

    $ scp -P 2264 gene.txt your_username@remotehost.edu:/some/remote/directory

Copy multiple files from the remote host to your current directory on the local host

    $ scp your_username@remotehost.edu:/some/remote/directory/\{a,b,c\} .

    $ scp your_username@remotehost.edu:~/\{gene.txt,cancer.txt\} .

scp Performance

By default scp uses the Triple-DES cipher to encrypt the data being sent. Using the Blowfish cipher has been shown to increase speed. This can be done by using option -c blowfish in the command line.

    $ scp -c blowfish some_file your_username@remotehost.edu:~

It is often suggested that the -C option for compression should also be used to increase speed. The effect of compression, however, will only significantly increase speed if your connection is very slow. Otherwise it may just be adding extra burden to the CPU. An example of using blowfish and compression:

    $ scp -c blowfish -C local_file your_username@remotehost.edu:~

Variant calling and/or genotyping

• DiscoSNP++ and discoSnpRAD: Reference-free small variant discovery (SNPs and indels)
• MindTheGap: Detection and assembly of large insertion variants
• TakeABreak: reference-free inversion discovery tool
• SVJedi: Structural Variant genotyper with long read data
• SVJedi-graph: Structural Variant genotyper with long read data using a variation graph

Sequence assembly

• MinYS: reference-guided genome assembly in metagenomics data
• MTG-link: local assembly tool for linked-read data
• Minia: De novo short read assembler
• de-novo pipeline: de-novo assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes
• Mapsembler2: Targeted assembly (not maintained)

Managing k-mers & indexation

• findere: simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
  • fimpera extends findere adding the abundance information.
• kmtricks: modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.
• kmindex is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.
• back to sequences: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.
• Backpack Quotient Filter: k-mer indexing data structure with abundance
• short read connector: Detect similar reads from potentially large read set
• DSK: Count K-mer in sequences

Pangenome graph manipulation

• Pancat: Pangenome Comparison and Analysis Toolkit
• GFAGraphs: a Python library to handle pangenome graph files in GFA format.

Comparative metagenomics with k-mers

• Simka and SimkaMin: Comparative metagenomics for large-scale datasets
• Comparead & Commet: comparison of metagenomic datasets

Species and bacterial strains identification

• ORI: software using long nanopore reads to identify bacteria present in a sample at the strain level
• StrainFLAIR: STRAIN-level proFiLing using vArIation gRaph

General-purpose sequencing data manipulation

• GASSST: long read mapper
• Leon: short read compressor (now included in GATB-core)
• Bloocoo: short read corrector
• BCALM: Construct compacted de Bruijn graphs (unitigs)

 Protein Structure

• A_Purva: Contact Map Overlap solver
• MD-Jeep: Distance Geometry solver
• CSA: Comparative Structural Alignment

Workflow

• SLICEE: parallel execution of bioinformatics workflows

Comparative Genomics

• CASSIS: detection of rearrangement breakpoints
• PLAST: intensive bank-to-bank sequence comparison
• DRJBreakpointFinder: detection and precise localization of excision sites in proviral segments

We are looking for a motivated candidate for handling proteomic and/or transcriptomic and other data with a strong background in bioinformatics tools and database development. The project will include identification of novel peptides from mass spectrometry-based proteomic data.

Familiarity with statistical tools or wet lab experience will be an added advantage. The position is open for immediate appointment and available for two years. The applicant will be appointed as Research Associate or Senior Research Fellow based on qualifications as detailed below:

Research Associate: Ph.D. in Biological Science or Bioinformatics with relevant publications in peer reviewed journals. Familiarity with bioinformatics tools, database development, programming skills and proteomic and/or other omics data analysis. Salary will be as per ICMR rules and guidelines.

Senior Research Fellow: M.Sc./B.Tech. in any branch of biology/ biotechnology/bioinformatics, with minimum 2 years of research experience (essential). Familiarity with bioinformatics tools, database development, programming skills and proteomic data analysis. Salary will be as per ICMR rules and guidelines.

Application will be shortlisted based on CV, reference letters from mentors and telephonic interview. Candidates will be called for a personal interview at Bangalore before appointment. No travel expense will be provided for attending interview at Bangalore.

Interested candidates may send a Letter of Interest and CV by email to: ravi@ibioinformatics.org on or before May 15th, 2014.

Contact:
Dr. Ravi Sirdeshmukh
Distinguished Scientist & Associate Director, IOB,
Principal Advisor MSMC/MSCTR

Advertisement: www.ibioinformatics.org/careers.php

minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta

This reports Racon's changes in a table. You can exclude indels with the -I option in show-snps. 

This process (Racon -> MUMmer -> SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).

(A) Senior Research Fellow (One Post): Emoluments as per DST/DBT norms.

Candidates having M.Sc. degree (with minimum of 55% marks) or equivalent in Life Sciences/Biotechnology/Bioinformatics/ Molecular Biology or any other related field with minimum of two years of post M.Sc. research experience are eligible to apply. The candidate having computer skill (Linux, Perl, Java, MySQL) and/or experience in advanced molecular biology, next generation sequencing data analysis and molecular markers analysis will be preferred.

The position is completely on temporary basis and co-terminus with the project. The initial appointment will be for one year, which can be curtailed/extended on the basis of assessment of the candidate’s performance and discretion of the Competent Authority. NIPGR reserves the right to select the candidate against the above posts depending upon the qualifications and experience of the candidates. Reservation of posts shall be as per Govt. of India norms.

Eligible candidates may apply by sending hard copy of completed application in the given format with a cover letter showing interest and attested copies of the certificates and proof of research experience. The applications should reach at the address given below within 15 days from the date of the advertisement. The subject line on envelope must be superscribed by “Application for the Post of SRF in DST - AISRF project”.

Note: ONLY hard copy of the application in the given format will be accepted.

Last date April 03, 2014

Dr. Mukesh Jain
Staff Scientist
National Institute of Plant Genome Research
Aruna Asaf Ali Marg, P.O. Box NO. 10531,
New Delhi - 110067

Advertisement: http://www.nipgr.res.in/careers/vacancies_latest.php#

A swift, versatile phylogenomic and high-throughput sequencing simulator https://jackalope.lucasnell.com

Address of the bookmark: https://github.com/lucasnell/jackalope

The interview will now be held 01st April 2014. The monthly fellowship of JRF will be Rs 12,000/- plus HRA as per the University rules.

Essential Qualification: Master degree in any discipline of Life Science with NET qualified or valid GATE score.

Desirable Qualification: Preference will be given to candidates having research experience in Bioinformatics.

The interested candidates should report for the Interview on 01st April, 2014 at 10:00 am in the Conference Room of Dean, School of Biotechnology, First floor, Gautam Buddha University, Greater Noida. Interested candidates may also send their resume to undersigned by postmail/e-mail shaktis@gbu.ac.in or shaktisahi@gmail.com. No TA and DA will be paid for appearing for the interview.

Dr. Shakti Sahi
(Principle Investigator)
School of Biotechnology
Gautam Buddha University
Greater Noida
Ph:9971791897

Advertisement:

www.gbu.ac.in/Recruitment/JRF_advertisement_DSTProject_Shakti_26March14.pdf

More at https://github.com/ekg/mutatrix

./mutatrix -S sample -P test/ -p 2 -n 10 reference.fasta

Address of the bookmark: https://github.com/ekg/mutatrix