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.

Center for Computational Natural Sciences and Bioinformatics

Junior Research Fellowship Position

Applications are invited for one JRF position in the following DAE sponsored project.

Title of the project: Insight into the Structure–Function Relationships of Chemically Modified Nucleic Acids: A Molecular Dynamics Simulations Study.

The above project involves theoretical modelling and simulations on chemically modified nucleic acids to investigate their structures, dynamics and thermodynamic stabilities.

Desired qualification: M.Sc. in Chemistry/ Bioinformatics; GATE/UGC-CSIR NET qualification.

To apply: Send detailed curriculum vitae by e-mail to the following address on or before 31 August 2015: Prof. U. Deva Priyakumar (devalab@iiit.ac.in), CCNSB, IIIT-H, Gachibowli, Hyderabad 500 032.

• Whole-genome sequencing
• Whole-exome sequencing
• RNA-seq (speical mode available)
• ChIP-seq

Address of the bookmark: http://qualimap.bioinfo.cipf.es/

Address of the bookmark: https://github.com/fenderglass/Flye

Eligible candidates may appear in Walk-in-interview for the positions of Senior Research Fellow in ICAR funded projects as follows

ICAR Network Project on Transgenics in Crops- Amelioration of cold induced sweetening in potato.

PI: Dr Debasis Pattanayak

SRF

Rs.25000/‐+ 30% HRA

September 29, 2015

Essential: Master’s Degree in Bioinformatics /Biotechnology/ Biochemistry/ life sciences with four years Bachelor’s Degree (or) Master’s Degree in Bioinformatics /Biotechnology/Biochemistry/ life sciences with NET qualification. .

Desirable: Experience in Bioinformatics and programming.

Age Limit: 35 years max. (5 years relaxation for SC/ST/OBC and woman candidates as per ICAR rules).

The post is purely temporary in nature and is co-terminus with the project. The interview will be held on September 29, 2015 at 10 AM at NRCPB, LBS Building, Pusa Campus, and New Delhi-110012. The candidates must bring four copies of biodata, original certificates, attested photocopies of each of the certificates and an attested copy of 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

http://www.nrcpb.org/sites/default/files/NPTC%20walk%20in%20interview%20September%202015%20for%20NRCPB%20webpage%20D%20%20%20Pattanayak.pdf

https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

Address of the bookmark: https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

Desirable : Research or teaching experience in Bioinformatics and Computational Biology.
Honorarium : Rs. 1,000/- per lecture (subject to a maximum of 25,000/- per month)
How to apply

Interested eligible candidates may attend the 'walk-in' interview along with all original certificates and testimonials with a copy of their bio-data. Walk-in-interview will be held on 28.09.2015 (Monday), 03:00 P.M. at the office of the Dean, School of Life Sciences, Science Block — I, Pondicherry University, Puducherry — 605 014. Candidates reporting after 03:00 P.M. will not be entertained.

More at http://www.pondiuni.edu.in/news/walk-interview-guest-faculty-centre-bioinformatics

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

Accompaniment to the Advertisement No. 52 dated 10.11.2015 for various Teaching Positions purely on contract basis for a maximum period of five years in the various Departments/Centre of the University.

Last date for receipt of application in the University Office is 04.12.2015.

Associate Professor

Environmental Science

Institute of Bioinformatics & Biotechnology (IBB)

Microbiology

Assistant Professor

Biotechnology

Institute of Bioinformatics & Biotechnology (IBB)

Microbiology

More Info : http://collegecirculars.unipune.ac.in/sites/documents/Job%20Openings/advt-no-52-dt-10-11-2015-contract-positions.pdf