Bactopia can be split into two main parts: Bactopia Analysis Pipeline, and Bactopia Tools.

Bactopia Analysis Pipeline is the main per-isolate workflow in Bactopia. Built with Nextflow, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.

Bactopia Tools are a set a independent workflows fo

Address of the bookmark: https://github.com/bactopia/bactopia

More at http://www.bioinsilico.org/

Abstract: Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.

In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.

Speaker: Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences

Details: Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST
Register here: http://www.strand-ngs.com/webinar_registration

Department of Genetics

University of Delhi South Campus

NEW DELHI – 110 021

WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT & LAB / FIELD ATTENDANT

1 Research Scientist (RS) – 3

DBT, Ph. D.

Experience on DNA Markers, plant genome mapping and bioinformatics

Salary: 60,000 (Consolidated) + 5% annual increment

Date and time: 25.06.2015 at 10:30 AM

These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’

The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.

Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.

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

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• Assembly of nanopore reads using Canu.
• Polish canu contigs using racon (optional).
• Map a paired-end Illumina dataset onto the contigs obtained in the previous steps using BWA mem.
• Perform correction of contigs using pilon and the Illumina dataset.

Address of the bookmark: https://github.com/nanoporetech/ont-assembly-polish

(ABT/DIC/01/2014 (No. AAU/ABT/DIT/Advt. 01/2015/111 Dtd. 19-05-2015)

Walk in interview for the following position will be held on 6th June, 2015 at 10.00AM in the Office Chamber of the undersigned. Candidates may appear for the interview with bio-data, reprints / publication / thesis etc and passport size photographs, original and attested copies of all testimonials etc, which must be presented at the time of interview. The applicants may submit their resume in advance tomkmodi@aau.ac.in.

Research Associate

Ph.D. in Biotechnology/ Bioinformatics. Or

Masters degree in Biotechnology/Bioinformatics with minimum 3(three) years research experience

Desirable : Experience in Bioinformatics as evidenced from published research

Rs 36,000+HRA for the 1st two years and 38,000+HRA for the 3rd year.

Senior Research Fellow

Master Degree in Biotechnology/ Bioinformatics. With 2 (two) years Experience in Bioinformatics as evidenced from Course work/ Diploma/Published research

Rs 28,000+HRA for NET qualified candidate/Professional degree holder

Rs 18,000+HRA for non-NET qualified general degree holder

Junior Research Fellow

Master Degree in Biotechnology/ Bioinformatics/Computer Science/Computer Application

Desirable: Experience in Bioinformatics as evident from Course work/ Diploma/Published research

Rs 25,000+HRA for NET qualified candidate/Professional degree holder

Rs 16,000+HRA for non-NET qualified general degree holder

Note: Term and conditions will be as per the DBT, Govt of India guidelines.

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Applications are invited for the post of Senior Research Fellow- SRF (1) and Junior Research Fellow- JRF (1) to be appointed in a SERB-funded major research project entitled “Biochemical and functional properties of Synechocystis Glutathione S-transferase(s)” sanctioned to Dr. Timir Tripathi, Molecular and Structural Biophysics Laboratory, Department of Biochemistry, NEHU, Shillong.

Essential Qualifications: For both positions M.Sc. or equivalent with a good academic record is a prerequisite.

For Project-SRF, experience in bioinformatics/computational biology is required, which should be evident by atleast one good publication.

For JRF position, freshers can also apply.

Stipend: As per SERB norms.

Interested students can email their detailed bio-data including mobile number and recent photograph to msb.biochem@gmail.com, latest by 20.06.15. The hard copy is not required. The date of interview will be informed after primary scrutiny of the applications. No TA/DA will be paid if called for interview. For details of the research work of the PI’s group kindly visit www.ttripathi.webs.com

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https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home

Address of the bookmark: https://github.com/clemgoub/dnaPipeTE

#Find the reverse complement of a DNA string.
#Given: A DNA string Pattern.
#Return: Pattern, the reverse complement of Pattern.

use strict;
use warnings;

my $string="AAAACCCGGT";
my $finalString="";
my %hash = (
    "C" => "G",
    "A" => "T",
    "T" => "A",
    "G" => "C",
);

for (my $aa=0; $aa<=(length($string)-1); $aa++) {
    my $char=substr $string, $aa, 1;
    #print $hash{$char};
    $finalString="$hash{$char}"."$finalString";
}

print $finalString;
print "\n";

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant