Address of the bookmark: https://github.com/dhlbh/BASE

Candidates having the below mentioned qualifications may appear for walk in interview at ICPO on 2nd December 2014 between 10.00 AM and 12:00 PM under the below time bound projects under Dr. Subhash M. Agarwal, Scientist C. The post is purely temporary and co-terminus with the project.

Research Assistant (One)
25650/- consolidated
Discovery of EGFR secondary mutant inhibitors using structure based screening approach (ICMR)
Duration: 7 months

Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record.

Desirable: Experience in scripting and molecular docking.

Below 30 years

Junior Research Fellow (One)

16,000 + 30% HRA = Rs. 20800/-

Identification of novel inhibitors targeting EGFR using an integrated ligand and structure based approach (DBT)

Duration: 9 months

Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record. Candidates with CSIR-UGC / ICMR, NET qualification will be preferred

Desirable: Experience in scripting, QSAR and molecular docking.

Below 28 years

Interested eligible candidates may send their applications with Bio-data by email at (smagarwal@gmail.com) or by post addressed to Dr. Subhash M Agarwal, Scientist C, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301 so as to reach latest by 1st December, 2014. The candidates may appear for interview at ICPO along with 3 copies of CV, photo and relevant certificates of qualifications in original and reprints of publications at the time of interview. It should be noted that No TA/DA will be paid for the walk in Interview.

Advertisement: www.icpo.org.in/advt-walk-in-interview.docx

For more background see also the publication at BMC Bioinformatics.

https://github.com/clwgg/nQuire

Address of the bookmark: https://github.com/clwgg/nQuire

http://bioinformaticsonline.com/videolist/watch/19555/a-3d-map-of-the-human-genome

Researchers have been working to determine how cells regulate gene expression for nearly as long as we’ve known about DNA. How, for example, do nerve cells know to turn off only nerve cell genes and turn off bone cell genes? DNA folding loops are part of the answer. This research team, which published their findings in a paper in Cell http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4 , found that the number of loops is much lower than expected. There are only 10,000 loops instead of the predicted millions, and they form on/off switches in DNA.

More at http://www.eurekalert.org/pub_releases/2014-12/ru-3mr121114.php

Reference http://www.cell.com/cell/abstract/S0092-8674%2814%2901497-4

gapFinisher can fill gaps in draft genomes quickly and reliably.

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

1 Dr. A.K.Mishra Coordinator & PI (BTISnet)

Traineeship (two) for one year

Rs. 5000/- (consolidated)

M.Sc. (Bioinformatics) with 60 % marks from a recognized University

20-12-2014 (10:00 AM -11:00 AM)

Studentship (four) for one year

Rs. 2500/- (consolidated)

Final year M.Sc./ M.Tech (Bioinformatics) Students from a recognized University

20-12-2014 (11:00 AM- 1:00 PM)

The positions are purely temporary and co-terminus with the DBT Programme. Eligible candidates are requested to submit the application form in the prescribed format along with original certificates/ documents (Degree, Marks sheets, Work experience, if any) at the time of interview. No TA/DA will be paid. Maximum age limit is 28 years for all positions. Age relaxation of 5 yrs for SC/ST and woman candidates and 3 years for OBC candidates will be given. Canvassing in any form invites disqualification.

Advertisement: http://www.iari.res.in/files/BIC-08122014-20141208-172344.pdf

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

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

Applications in plain paper are invited for the posts of (1) Traineeship (2 Nos.) and (2) Studentship – (2 Nos.) in the DBT funded-Bioinformatics Infrastructure Facility (BIF), Nagaland University, Lumami-798627, Nagaland. Details are given below. Interested candidates may submit the application along with self attested copies of certificates in support of the candidature to Prof. Chitta Ranjan Deb, Coordinator or Dr. L. N. Kakati, Deputy Coordinator, BIF Centre, Nagaland University, Lumami-798627, Nagaland on or before 15th January 2015.

The scanned application with relevant documents may be sent by email attachment to bifnulumami@gmail.com. Shortlisted candidates will be informed by email if called for interview. No TA/DA is admissible for attending the interview.

Traineeship (Two nos.)

Post Graduate degree in any branch of Life Sciences from UGC recognized Universities

Knowledge of computers and bioinformatics

Rs.8000/- p.m. fixed.

6 months

Studentship (Two nos.)

Pursuing Post Graduate degree in any branch of Life Sciences from UGC recognized Universities

Knowledge of computers and bioinformatics

Rs.8000/- p.m. fixed.

6 months

Terms and Conditions:

i) Applicants need to produce all original documents if call for interview.
ii) The posts are purely temporary and the appointment does not confer any entitlement or right over the job and will not be considered as formal service.
iii) No TA & DA will be paid for appearing in the walk-in-interview.
iv) The stipend/salary amount is subject to the sanction of DBT, New Delhi.

Advertisement: http://www.nagauniv.org.in/files/BIF%20Advt.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.