1. Earth BioGenome Project (EBP) - A global effort to sequence and annotate roughly 1.5 million known eukaryotic species and create a comprehensive reference library of Earth's biodiversity.
2. Vertebrate Genomes Project (VGP) - Focuses on producing high-quality reference genomes for vertebrate species, providing a major foundation for the wider Tree of Life.
3. Darwin Tree of Life - A UK and Ireland initiative aiming to sequence approximately 70,000 species, creating a detailed genomic map of regional biodiversity.
4. African BioGenome Project (AfricaBP) - A pan-African initiative focused on sequencing Africa's biodiversity while strengthening genomics and bioinformatics capacity across the continent.
5. European Reference Genome Atlas (ERGA) - A European effort to generate high-quality reference genomes for Europe's biodiversity and connect national sequencing efforts.
6. Canada BioGenome Project - Building reference genomes for Canadian biodiversity, supporting conservation, research and the study of ecosystems.
7. California Conservation Genomics Project - Uses genomics to understand and protect California's biodiversity and help inform conservation decisions.
8. Bat1K - An ambitious global effort to sequence the genomes of all known bat species, helping scientists study their evolution, longevity, immunity and unique biology.
9. Bird 10,000 (B10K) - A global project aiming to create genome resources covering the world's bird diversity and reconstruct avian evolutionary history.
10. Global Invertebrate Genomics Alliance (GIGA) - Builds genomic resources for the enormous and genetically diverse world of invertebrates.
11. GenomeIndia - India's national human-genome initiative, designed to capture the country's extraordinary population diversity and create a reference resource for Indian genomics.
12. All of Us Research Program - A US national research program combining genomic information with health and lifestyle data at population scale.
13. 1+ Million Genomes / Genome of Europe - A European effort to enable secure, cross-border use of genomic and health data and develop genome-scale resources involving more than one million people.
14. Korea National Integrated Bio Big Data Project - South Korea's large-scale national effort combining genomic and health information from a very large population cohort.
15. Saudi Genome Program - A national genomics initiative focused on genetic diseases, population genomics and precision medicine in Saudi Arabia.
16. Australian Genomics / Genomics Health Futures Mission - Australia's growing investment in genomic medicine, rare disease research and population-scale health genomics.

To read the manual, please click the link https://askarbek-orakov.github.io/ASAR/

Address of the bookmark: https://github.com/Askarbek-orakov/ASAR

More at http://www.babraham.ac.uk/our-research/nuclear-dynamics/

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.

Applications are invited for the post of Junior Research Fellow (JRF) in a DBT funded IYBA project entitled “Generatingaprotein-ncRNA interactome for Dorsal mediated gene regulation and dorso-ventral patterning genes in Drosophila” in the Lab. Of Molecular Biology at the Faculty of Life Sciences and Biotechnology, South Asian University, New Delhi. The project requires extensive use of molecular, genetic and genomic approaches.

POST: Junior Research Fellow (JRF)

NO. OF VACANCIE(S) - (01)

FELLOWSHIP: Rs. 16,000/- plus HRA

PROJECT DURATION: 2014-2016 (Two years)

LAST DATE FOR APPLICATION: Aug 18, 2014.

Eligibility criteria:

M.Sc./M.Tech./ in Biological Sciences/Biotechnology/Bio-Informatics. Candidates with research experience in the field of Drosophila/Yeast genetics will be preferred.

Application Procedure:

A covering letter along with your CV, copy of prior publications (if any) and proof of experience should be e-mailed to lmb_sau@aol.com. Hardcopy of the application should be brought on the day of interview along with other testimonials and marks statements for verification purpose.

IMPORTANT NOTE:

-No TA/DA will be paid for attending the interview.

-SAU may select candidates against the post depending upon qualification and experience of candidates and reserves the right to relax any of the qualifications in case the candidate is found otherwise well qualified by the Selection Committee

-The abovementioned post is temporary and will be initially offered for a period of one year and can be extended, on satisfactory performance.

More at http://www.sau.ac.in/recruitment/vacancy.html

Research Scientists within the Bioinformatics Program are involved in research related to cutting edge genomics and analysis of omics data. The research will utilize concepts, theories and best practices obtained from bioinformatics discipline and applied to biological and other biomedical data for analysis. The role may also involve designing databases, algorithm and/or computation methods for analyzing genomics and other omics data. The scientist will be working closely with the Translational Medicine Program within a state-of-the art research setting.

Please check the details of the opening and apply here: http://careers.sidra.org/sidra/Vacan...acancyID=60181

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