This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.

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

Jr. Research Fellow – 2 posts

Fellowship : Rs. 25000/- + 20% HRA pm for Ist & 2nd year and Rs.28000/- + HRA on 3rd year

Qualification : Ist class Masters Degree in Microbiology/Fishery Microbiology/Bio-technology.

Desirable :

1. CSIR/UGC NET/JRF qualified

2. Excellent analytical skills and computer documentation

3. Prior experience in handling microbial cultures and molecular techniques

Project Assistant – 1 post

Fellowship : Rs.8000/- p.m (consolidated)

Qualification: Masters degree in Microbiology/Biotechnology with skill in Bioinformatics

Desirable: Excellent analytical skills in Bioinformatics and computer documentation

Terms & Conditions:

Registration will begin at 8.30 a.m and will close at 11.00 am
Age limit (as on 29.1.2015): Below 35 years for men and 40 years for women.
Age relaxation of 3 year for OBC candidates and 5 years for SC/ST candidates is permissible.
Candidates are required to submit self-attested copies of all the Certificates in support of their claims regarding age, educational qualifications, scheduled caste/scheduled tribe/OBC etc. The original certificates shall be produced for verification before the interview.
Candidates should bring detailed bio-data (in the enclosed format) affixing a recent passport size photograph.
The selected candidate will be recruited on contract basis under ICAR norms. The post is purely temporary and is co-terminus with the project.
The candidates attending the interview should ensure that they fulfil all the eligibility conditions. No correspondence will be entertained from the candidates for selection/test/appointment.
No TA/DA will be paid to attend the interview.
Canvassing in any form will render the candidate disqualified for the post.
The Director’s decision will be final and binding in all aspects regarding the selection to the post.

Venue: CIFT, Matsyapuri.P.O, Cochin Date of interview: 29.01.2015 Time: 10.00 am

http://www.cift.res.in/uploads/userfiles/file/file/srf%20appn.doc

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: “Genome-scale metabolic modeling and simulation of rumen methanogens An in silico attempt to methane attenuation”

Funding Agency: University Grants Commission, New Delhi

Tenure of the project: Two years or till the end of the project period.

Position: Project Assistant (1 no.)

Essential qualification: First class M.Sc. in Bioinformatics/Microbiology/ Biotechnology and other related discipline.

Desirable qualification: Experience in an area relevant (Molecular Systems Engineering) to the project.

Fellowship: Rs. 5000 per month as per the UGC norms.

Upper age limit: 28 years

Date of Venue of interview: 22.01.2015, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli -620 024, Tamil Nadu

The above post is purely temporary and will be terminated with three month notice.

The Terms and the condition of the appointment shall be governed according to UGC, Govt. of India. The eligible candidates will bring their original certificates and documents at the time of interview. No TA/DA will be paid for attending the interview.

Dr. P. CHELLAPANDI
UGC-Research Awardee,
Department of Bioinformatics,
School of Life Sciences,
Bharathidasan University,
Tiruchirappalli -620 024, Tamil Nadu

Advertisement: www.bdu.ac.in/adv/PA_UGC_Bioinformatics.pdf

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

Bio-Linux is using an Ubuntu LTS version as its base

The fact that it uses Ubuntu LTS versions for the base is a good thing because it means its users won't have to worry about the support. Ubuntu 14.04 LTS is supported until 2019, so people who are using Bio-Linux shouldn't have a problem.

"An updated Bio-Linux 8 version is now on the website in ISO and OVA versions. As usual, there is no need to download this version if you are an existing user. All updates to existing packages will be applied to your system through the update manager and new packages are all available via apt-get or Synaptic," reads the announcement.

The changelog also states that a problem that was preventing the desktop to not start on VirtualBox has been fixed, the QIIME and Bowtie-Bio tools have been upgraded, the pandaseq paired end assembler has been added, and the beginners tutorial specific to Bio-Linux 8 has been improved.

Check out the official announcement for a complete list of changes and updates. You can download Bio-Linux 8.0.5 right now from Softpedia and give it a spin. It has the Unity desktop and now it runs very well in virtual environments.

Reference @ http://news.softpedia.com/news/Bioinformatics-Distro-Bio-Linux-8-0-5-Now-Available-for-Download-469867.shtml

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

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

Transcription is the process by which the information in DNA is copied into messenger RNA (mRNA) for protein production. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: The Central Dogma of Molecular Biology: "DNA makes RNA makes protein" Here the process begins. Transcription factors assemble at a specific promoter region along the DNA. The length of DNA following the promoter is a gene and it contains the recipe for a protein. A mediator protein complex arrives carrying the enzyme RNA polymerase. It manoeuvres the RNA polymerase into place... inserting it with the help of other factors between the strands of the DNA double helix. The assembled collection of all these factors is referred to as the transcription initiation complex... and now it is ready to be activated. The initiation complex requires contact with activator proteins, which bind to specific sequences of DNA known as enhancer regions. These regions may be thousands of base pairs distant from the start of the gene. Contact between the activator proteins and the initiation-complex releases the copying mechanism. The RNA polymerase unzips a small portion of the DNA helix exposing the bases on each strand. Only one of the strands is copied. It acts as a template for the synthesis of an RNA molecule which is assembled one sub-unit at a time by matching the DNA letter code on the template strand. The sub-units can be seen here entering the enzyme through its intake hole and they are joined together to form the long messenger RNA chain snaking out of the top.

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