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.

Project Title : "Structural and functional characterization of serine biosynthetic pathway enzymes from Entamoeba histolytica"

No. of Post : 01

Qualification : Ph.D in any computational biology / bioinformatics

Desirable : 1. Experience with docking, simulations and structural biology with proof of publications is preferred. 2. National Eligibility Test cleared [CSIR/UGC] candidate is preferred.

Salary : According to CSIR rules
How to apply

The application on plain paper indicating name, date of birth/age, address, essential/technical/professional qualifications. experience, list of publications should reach The Prof. S. Gourinath, Principal Investigator, [Project Director], School of Life Sciences, Jawaharlal Nehru University, New Delhi-110067, on or before 23rd May 2016.

More at http://www.jnu.ac.in/Career/currentjobs.htm

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

Eligibility : Pursuing final year of M.Sc./M.Tech.

Subject category for training : I. Agricultural biotechnology II. Computational biology and bioinformatics III. Food Science & Technology IV. Nutrition Science & Technology

Duration of Training : 6 months (January to June 2016)

Selection Procedure : Through screening and selection based on merit, experience, and expression of interest submitted by candidates
How to apply

The last date of application to reach NABI latest by November 30, 2015 by 5:30 PM

More at http://www.nabi.res.in/Training.aspx

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

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

Project entitled: "Establish of Bioinformatics Facility for biology teaching through bioinformatics"

Name of post: Research Associate /Trainees

Number of post: 03

Educational Qualification and Experience: Candidates should have Ph D in relevant subjects with experience in handling computational biology resources and software

Selection mode: Walk in interview

How to apply?
Interested and eligible candidates may appear for a walk-in interview on 14th November 2015 at 11.00 am, in the office of Director, Centre for Bioinformatics along with CV and attested copies of all testimonials and additional qualifications.

Recruitment reference: http://www.mdurohtak.ac.in/pdf/career/adv_research_asso_dbt_bioinfo.pdf

More at https://software.broadinstitute.org/gatk/download/bundle

ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/.

ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/

Address of the bookmark: https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1

Rajiv Gandhi Centre for Biotechnology (RGCB) invites applications for the following three faculty scientist positions:

Scientist G in any of the following disciplines of disease biology: Cancer Research/Cardiovascular Biology/Diabetes Biology/Pathogen Biology
Scientist E-II or F in Bioinformatics & Computational Biology
Scientist E-I or E-II in Cancer Research with special emphasis on Human Papillomavirus Research

More at http://rgcb.res.in/wp-content/uploads/2015/11/APPLICATION-FORMAT-FOR-SCIENTISTS.docx

http://i-pv.org/ipv_rec

Address of the bookmark: http://i-pv.org/

More at

https://www.isas.de/files/redaktion/jobs/2021/18.60.1_Postdoc_deNBI_06_21_AS.pdf

https://www.isas.de/en/news/062021-post-doctoral-position-scientist-mfd-in-bioinformatics