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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• DNA-mapping*
• ChIP-seq*
• RNA-seq*
• ATAC-seq*
• scRNA-seq
• Hi-C
• Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

(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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gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

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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Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

#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";

Project Scientist-I
Experimental / Computation analysis experience in highthroughput genomics/ clinical application.

Project Manager
Experience in handling large biological projects involving high-throughput genomics/ clinical application.

Scientific Administrative Assistant
Lab Work.

More at https://vinodscaria.genomes.in/positionsopen

Monthly fellowship (in rupee): 5,000/-

Traineeship

First Class M.Sc Bioinformatics/ Biotechnology/ Botany

Studentship: 5,000/-

M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.

Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.

Interested candidates may appear for walk-in-interview on 16th June 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am

More at http://www.jntbgri.in/jntbgri/news/File0001.pdf

The "Ifs" of NGS QC and Trimming

1. Ensures Data Integrity
   If you want to minimize errors in downstream analyses, QC and trimming remove low-quality reads and bases, ensuring high-confidence data. This step is essential for reliable variant calling, assembly, and other applications.

2. Removes Contaminants
   If adapter sequences or contaminants are present in the raw reads, trimming can eliminate them. This prevents issues like misalignment or incorrect biological interpretations, ensuring cleaner data for analysis.

3. Improves Mapping and Assembly
   If your goal is better alignment to a reference genome or improved de novo assembly, trimming low-quality bases and adapters is critical. High-quality reads map more efficiently and generate more accurate assemblies.

4. Reduces Computational Load
   If you want to save computational resources, trimming reduces the dataset size, which speeds up processing and analysis. Clean datasets mean less computational time spent on processing low-quality data.

5. Prepares for Standardized Analyses
   If your project involves multiple datasets, QC and trimming ensure uniformity across them. This standardization makes comparisons valid and reproducible, particularly in large collaborative studies.

The "Buts" of NGS QC and Trimming

1. Risk of Over-Trimming
   But excessive trimming can lead to the loss of informative sequences, reducing read depth and potentially discarding biologically relevant data. This is especially critical in studies with limited sequencing depth.

2. Bias Introduction
   But trimming algorithms might introduce biases, especially if they inadvertently remove sequences with specific biological patterns. This can skew results and compromise biological insights.

3. Loss of Context in Paired-End Reads
   But trimming one read in a pair more than the other can lead to loss of pairing information. This complicates downstream analyses that rely on paired-end data, such as structural variant detection.

4. Time and Resource Intensive
   But running QC and trimming for large datasets can be computationally expensive and time-consuming. As sequencing depth increases, preprocessing becomes a bottleneck in the analysis pipeline.

5. Variable Standards
   But the criteria for trimming (e.g., quality threshold, minimum read length) can vary between tools and datasets. This variability may affect reproducibility and comparability of results across studies.

Balancing the "Ifs" and "Buts"

To maximize the benefits of QC and trimming while mitigating the challenges, consider the following best practices:

• Use QC Tools Wisely: Start with tools like FastQC to identify quality issues in your raw data. Visualizing quality metrics helps tailor your trimming parameters.

• Choose Reliable Trimming Tools: Tools like Trimmomatic, Cutadapt, and BBduk offer adaptive and customizable trimming options. Select one that aligns with your dataset and project goals.

• Set Reasonable Parameters: Avoid over-trimming by setting quality thresholds and minimum read lengths that balance data retention and quality improvement.

• Test Downstream Effects: Validate the impact of QC and trimming on downstream analyses, such as alignment efficiency, variant calling accuracy, or assembly quality.

• Document Your Workflow: Maintain detailed records of the parameters and tools used for QC and trimming. This ensures reproducibility and enables better troubleshooting.

Conclusion

NGS quality control and trimming are essential steps to ensure reliable and accurate data for analysis. While the "ifs" highlight the clear benefits of these steps, the "buts" remind us of the potential pitfalls. By adopting best practices and carefully balancing these considerations, you can optimize your preprocessing workflow and unlock the full potential of your sequencing data.