Developper: Gaëtan Benoit, PhD, former member of the Genscale team at Inria.

Contact: claire dot lemaitre at inria dot fr

Simka and SimkaMin are comparative metagenomics method dedicated to NGS datasets. https://gatb.inria.fr/software/simka/

Address of the bookmark: https://github.com/GATB/simka

Duration: 1 year

Funding Source: Institutional
Salary on grant: B2 (€ 22.000/year gross)
Contact Person (Referent): Tommaso Mazza
Ref. E-Mail: t.mazza@css-mendel.it
Tel: +39 06 44160526
Fax: +39 06 44160548

Job Description: The bioinformatics unit at IRCCS Casa Sollievo della Sofferenza - Mendel laboratory in Rome is looking for one young PhD bioinformatician with specific experience and/or interest in the analysis of transcriptomic data.

The candidate will be mainly in charge of developing research on a range of hot applications and projects, dealing with microarrays, RNA-Seq and miRNA-Seq data. Main activities will be: (i) data analysis (short-reads mapping, variants call and annotation, functional enrichment analysis of gene expression data); (ii) networks analysis and simulation (artificial knockout, redundancy and lethality analysis, gene set essentiality); (iii) developing of ad-hoc software solutions/routines on clusters of CPUs and GPUs.

The correct cultural background (training in Biology / Computer Science / Statistics or a mix of the three) and a strong interest in working with high throughput data analysis will be considered at the same level of specific experience in the above-mentioned fields.
Knowledge of molecular modeling and simulation and one of these languages: python, perl, R, Java, C++, C# is a golden plus. Good knowledge of Scientific English will be positively evaluated for this position, together with good presentation and teamwork skills.

A CV with one professional reference, details on educational background and of the biological and/or bioinformatic and/or data analysis skills and experience should be sent by email for a preliminary selection to: Tommaso Mazza, CSS-Mendel: t.mazza@css-mendel.it

Context
Casa Sollievo della Sofferenza is an Institute for hospitalization, care, and scientific research located in San Giovanni Rotondo, Italy. It integrates clinical assistance (with inpatient and outpatient facilities) and research. It has an affiliate institute, CSS-Mendel, located in Rome. Between the two sites, it employs over 100 researchers who focus on genetics. The Center is equipped with state of the art genomics technology (SOLiD 5500XL next generation sequencer, Illumina MiSeq, Affymetrix/Agilent microarray platforms, etc) as well as a dedicated high performance computing facility, a non-conventional workstation of GPUs and a short- and long-term storage disk.

Applications
Candidates should send:
• a cover letter explaining the role they would like to undertake within the Center, even if it is not listed in this job adv, stating clearly why they would be a good fit to the proposed role, and what they would bring to the Center in terms of expertise, ideas, talent;
• a CV including a list of publications;
• List of referees;

More at http://www.css-mendel.it/

gapFinisher can fill gaps in draft genomes quickly and reliably.

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

1. Work to establish improved quantitative experimental assays (such as microarrays or differential in-gel electrophoresis) and
2. Development of modern computational methods (such as hierarchical probabilistic models or integration of heterogeneous data sources)

Lab page @ http://bioinf.boku.ac.at/

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

Please add ur links/bookmarks in comment section.

Address of the bookmark: http://physicsdatabase.com/free-math-books/

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

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/23/14/1713.full

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.

CENTRE FOR BIOINFORMATICS

PUDUCHERRY

Applications are invited for one Project Assistant to work in the UGC sponsored Research Award "Molecular Docking and Dynamics studies to understand the interacting mechanism of oncogenic 101 protein with its cellular proteins".

The duration for the fellowship is 12months only with consolidated pay ofRs. 5,000 per month.

Application on plain paper with following details: Name, Address, Data of Birth, Father's Name, Nationality, Educational Qualification (SSLC onwards-enclose attested copies of certificate) and Researcb Experience may be addressed to Dr. R. Krishna, Principle Investigator (PI), UGC Research Award, Centre for Bioinformatics, Pondicherry University, Pondicherry - 605 014.

Application should reach in January 261h , 2013.

Essential Qualification: M.Sc. in Bioinformatics/Biophysics with good academic record.

Qualification for Project Fellow:

M.Sc in Bioinformatics/Biophysics.

The person to be considered for appointment as Project Fellow must have second class master degree with a minimum of 55% marks in the subject concerned or a related subject.

The candidate to be appointed as Project Fellows should be below thc age of40 years at the time of appointment.

Desirable Qualification for this Project: Research Experience in Small/Macromolecule Crystallography and Structural Bioinformatics.

For more details, refer the web site: www.pondiuni.edu.in/sites/default/files/BIC-311213.pdf