Essential qualifications for JRF
: M. Sc. in Bioinformatics with experience in Proteomics, genomics and structural biology. Knowledge of programming language, pearl and database – HTML, CSS,php and Java script.
Essential qualifications for Research Associate:
MSc/MTech in Bioinformatics with three years experience or Ph.D in Bioinformatics with experience in proteomics, genomics and structural biology. Knowledge of programming language, perl and database
– HTML, CSS, Java script. NGS sequence assembly and analysis and algorithm designing.
Age limit : 35 years maximum (5 year relaxation for SC/ST and women candidates)
Emoluments:
JRF: 16,000 + 30% HRA
.
Res Assoc: Rs22,000 + 30% HRA
The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.
Interested candidates
should send the duly filled application forms (format in the following page ) so as to reach on or before 20.9.2014 along with all the relevant documents.

More at http://www.iari.res.in/files/JRF_RA-03092014-20140903-135319.pdf

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

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.

ADVERTISEMENT NO. - URDIP/ 5/2014

Learning opportunity for young Science and Engineering professionals to make a career in Information Science Industry CSIR has set up a Unit for Research and Development of Information Products (CSIR-URDIP) at Pune to work in the area of Scientific Informatics (ChemBioinformatics/Patent Informatics/Phytoinformatics/Toxinformatics) and related
software development projects.

Applications are invited from CSIR - UGC NET Qualified Candidates for consideration as Project Fellow (PF) and/or Senior Project Fellow (SPF) based on the experience to work on existing and new projects at CSIRURDIP.

Project Fellow

Remuneration - (Rs. 16,000.00 + 20% HRA)

M. Sc. In Biochemistry/Microbiology/Bioinformatics [Post-code A02] only with minimum of 55% marks

Senior Project Fellow

Remuneration - (Rs. 18,000.00 + 20% HRA)

M. Sc. in Biochemistry/Microbiology/Bioinformatics [Post-code A05] only with minimum of 55% marks plus two years research or relevant informatics experience

Please visit www.urdip.res.in/career.htm to apply online by 30th September, 2014.

Successful candidates who have appeared for NET exam in 2012 and 2013 are only eligible to apply.

Advertisement: http://115.112.95.114/urhr/download/Advt5_2014.pdf

minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta

This reports Racon's changes in a table. You can exclude indels with the -I option in show-snps. 

This process (Racon -> MUMmer -> SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).

Eligible candidates are invited for a walk-in-interview for recruitment of Project Assistant in SVIMS Bioinformatics centre under the BTISnet Project entitled “Creation of Bioinformatics Infrastructure Facility for promotion of Biology teaching through Bioinformatics” on 25.09.2014 at 11 AM in SVIMS, Tirupati. The engagement will be made purely on temporary basis for a period of one year and it can be terminated at any time without notice or without assigning any reason thereof by the Coordinator of the Project. The person engaged shall not be entitled for any claim implicit or explicit for absorption in the University.

1. Name of the post : Project Assistant

2. Qualification :
i) Essential : MSc Bioinformatics/MTech (Biotechnology/Bioinformatics)

ii) Desirable : Experience in Bioinformatics research work (Preference will be given to candidates qualified in BINC/UGC/CSIR/NET/GATE)

3. Remuneration : 16000 + 10% HRA for NET/GATE candidates 14000 + 10% HRA for M. Tech / M.Sc. Candidates

4. Place of posting : Tirupati

5. Duration of the Project : One year

Terms and conditions:

1. Candidates are required to submit the Biodata relevant certificates in support of their age and educational qualification etc., before the interview committee, SVIMS University, Tirupati.

2. Candidates called for interview will attend the interview at their own cost.
3. Interim enquiries will not be entertained.
4. The maximum age limit for Project Assistant is 28 years for general category and 33 years for SC and ST category candidates as on 25th September, 2014.

Advertisement:

http://svr98.ehostpros.com/~svimsb98/Project%20Assistant_notification.pdf

We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.

Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.

https://github.com/gwct/referee

Address of the bookmark: https://gwct.github.io/referee/#

More http://www.nieduszynski.org/index.php
http://www.path.ox.ac.uk/research/cell-biology-and-pathology/conrad-nieduszynski-group

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

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

Please visit our site at www.arraygen.com