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

Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology & Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of
the project.

Essential Qualification

For Research Fellow:-

M.Sc. in Systems Biology and Bioinformatics / Life Sciences with minimum 55% marks.

Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

For Program Assistant:-

The candidate must have M.Sc./M.Tech/MCA/PGDCA in Computer Science and must be able to handle LAN, Linex. Preference will be given to the candidate having experience in
System Administration.

Emoluments

For Research Fellow Rs. 12,500/- per month (Fixed)
For Program Assistant Rs. 12,500/- per month (Fixed)

Applications should be reach on or before 19-11-2014 in the office of the undersigned.

Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

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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

Reference Number IIT/SRIC/R/DIC/2014/314, DATED 28thNovember, 2014

Temporary Position(s)

i) Junior/ Senior Project Officer (1)
ii) Junior Project Assistant (2)

Consolidated Compensation

i) Rs.16,000/- to Rs.18,000/- p.m. (depending on qualification & experience)
ii) Rs.8,000/- to Rs.10,000/- p.m. (depending on qualification & experience)

Coordinator / PI Dr. Sudip K. Ghosh, Dept of Biotechnology.

Department / Centre / School Dept of Biotechnology

Qualifications & Experience

(i) M. Sc in any branch of Life Sciences with experience in Molecular Biology/Genetics/Biochemistry preferably a Post Graduate diploma in Bioinformatics or two years working experience in bioinformatics (Minimum 60% marks starting from matriculation examination).

(ii) B. Sc. /B.A. /B. Com/Diploma in Management or Computer Science. Knowledge in computer software will be preferred (minimum 50% marks starting from matriculation examination).

More Information

Interested eligible persons may apply on plain paper, giving full bio-data along with attested copies of testimonials to the undersigned on or before 11thDecember, 2014.

Sponsor DBT, NEW DELHI

Last Date 11 Dec 2014

Application Fee Demand Draft for Rs.50/- (Not for female candidates) drawn in favour of IIT Kharagpur payable at Kharagpur

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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.

Address of the bookmark: https://github.com/broadinstitute/VariantBam

• Binaries for Linux/macOS
• From sources for Linux/macOS
• From sources for Windows

Address of the bookmark: https://github.com/imgag/ngs-bits

Originally design to map the location of objects in a 10 km map IrishGrid includes:

• native support of the Irish Grid System (see http://www.osi.ie/)
• optimize for speed (there's as less as possible data to conversion)
• customized color functions

https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl

Address of the bookmark: https://code.google.com/p/irishgrid/