http://ritg.med.harvard.edu/training/perl/RC_Perl_Intro.pdf

This bookmark is created to provide NGS online books links.

Address of the bookmark: http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version

What are SNPs?
SNPs (pronounced "snips") are positions in the genome where individuals differ by a single nucleotide. For example:

Reference: ...A T G C A T G A...
Variant:     ...A T G T A T G A...

Here, the C in the reference genome has been replaced by a T in the variant.

SNPs occur roughly every 300–1,000 bases in the human genome, meaning there are millions of them scattered throughout our DNA. Most SNPs have no effect on health, but some are linked to disease susceptibility, drug response, and other traits.

Why Do We Analyze SNPs?
1. Medical Genetics

Identify disease-associated variants (e.g., BRCA1/2 in breast cancer).

Predict drug response (pharmacogenomics).

Enable precision medicine by tailoring treatments.

2. Population Genetics & Ancestry

Trace human migration and ancestry.

Study genetic diversity within and between populations.

3. Agriculture & Animal Breeding

Select for desirable traits (drought resistance, yield, disease resistance).

Improve breeding efficiency in livestock.

4. Evolutionary Biology

Track natural selection.

Study adaptation in wild populations.

How is SNP Analysis Performed?
SNP analysis can be broadly divided into three steps:

SNP Detection
Genotyping arrays: Chips that test hundreds of thousands of known SNP positions simultaneously. Fast and affordable, widely used in consumer ancestry testing.

Whole-genome or whole-exome sequencing: Can detect known and novel SNPs across the genome.

Targeted sequencing or PCR: For focused analysis of specific regions.

Variant Calling
Sequencing data is aligned to a reference genome. Bioinformatics tools (e.g., GATK, bcftools) identify positions where the sequenced sample differs from the reference.

Annotation and Interpretation
Tools (e.g., SnpEff, VEP) predict the functional impact of SNPs.

Are the SNPs in coding regions? Do they cause amino acid changes? Are they known to be pathogenic?

Databases like dbSNP, ClinVar, and GWAS Catalog provide information on known associations.

Common Tools for SNP Analysis
Alignment: BWA, Bowtie2

Variant Calling: GATK, FreeBayes

Visualization: IGV, UCSC Genome Browser

Annotation: SnpEff, VEP

Statistical Analysis: PLINK, SNPTEST

Challenges in SNP Analysis
False positives/negatives: Sequencing errors, alignment issues.

Population stratification: Confounding in association studies.

Interpretation: Many SNPs have unknown or complex effects.

Researchers address these with rigorous quality control, large datasets, and increasingly sophisticated statistical models.

The Future of SNP Analysis
With advances in sequencing technology and AI-driven analysis, SNP studies are expanding:

Polygenic risk scores predict disease risk based on thousands of SNPs.

Large-scale biobanks (e.g., UK Biobank, All of Us) enable powerful genome-wide association studies (GWAS).

CRISPR and functional assays help validate SNP effects in the lab.

SNP analysis is at the heart of the genomic revolution, promising insights into biology, health, and evolution at unprecedented scale.

Conclusion
From diagnosing rare diseases to designing better crops, SNP analysis is a foundational tool in modern science. As our ability to sequence and interpret genomes improves, so will our understanding of these tiny—but mighty—variations in DNA.

1. FASTA
2. FASTQ
3. SAM
4. BAM
5. VCF
6. GFF
7. GTF

Address of the bookmark: https://bioinformatics.uconn.edu/resources-and-events/tutorials/file-formats-tutorial/

Address of the bookmark: https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html

Please visit our site at www.arraygen.com

Essential qualifications: First class M. Sc. in any branch of life sciences and qualified CSIR-UGC NET/GATE Examination.

Desirable qualifications: Practical experience in biochemical and biophysical studies of proteins

Emoluments: as per DBT norms

The project is tenable for two years, initially for one year.

Age: Below 28 years (relaxable in the case of SC/ST/OBC/women candidates)

Candidates are requested to bring two sets of complete applications on plain paper furnishing bio-data and copies of attested certificates along with originals (for verification) on the date of interview.

No TA/DA is admissible for candidates appearing at the interview.

Dr. Rajat Banerjee
Assistant Professor
Department of Biotechnology and
Dr. B. C. Guha Centre for Genetic Engineering and Biotechnology
University College of Science
35, Ballygunge Circular Road
Kolkata 700019

Advertisement: www.caluniv.ac.in/news/jrf_biotech_2.pdf

Central University of Jharkhand has been granted funds by the Department of Biotechnology (DBT), Govt. of India to establish “DBT-Boost to CUJ Interdisciplinary Life Sciences Departments for Education and Research” Applications are invited for the Assistant Professor on purely temporary basis. The appointments shall be initially for a period of one year, renewable every year depending on the satisfactory performance, till the end of project.

Position: ASSISTANT PROFESSOR (Total 03)
Salary: 45,000/- (fixed) per month
Essential Qualifications: i. Good academic record with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the master’s degree level with specialization in Biodiversity and Systematic/ Systems Biology/ Biophysics/ Bioinformatics from an Indian University, or an equivalent degree from an accredited foreign university. ii. Besides fulfilling the above qualifications, the candidates must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/SET. iii. Notwithstanding anything contained in i. and ii. candidates, who are or have been awarded Ph.D Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulation, 2009, shall be exempted from therequirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor. iv. NET/SLET/SET shall also not be required for such disciplines for which NET/SLET/SET in not conducted.
Desirable: Preference will be given to candidates having Ph.D in any of the above mentioned areas with NET

IMPORTANT DATES TO REMEMBER :

Last Date to Apply for this job 24/3/2015

REFERENCE:

Central University of Jharkhand (CUJ) Recruitment 2015 – Advt. No.: CUJ/Advt./14-15/15 Date: 26th Feb. 2015.

More at http://cuj.ac.in/careers.php

http://molbiolabccsumrt.webs.com/

Applications are invited for one post of RA in a DBT funded research project “Creation of Bioinformatics Infrastructure Facility (BIF) for the promotion of Biology Teaching through Bioinformatics (BTBI) Scheme of BTISet”.

Candidate should have a Ph.D. degree in Bioinformatics/Biotechnology/Genetics and Plant Breeding with adequate experience in the area of Bioinformatics. If a suitable candidate for the post of RA is not available, a JRF/SRF may be appointed.

Candidate for the post of JRF/SRF should have Master’s degree in relevant subject with adequate experience in the area of Bioinformatics and should be NET/DBT-BINC qualified

Interested candidates may send their bio-data to Prof. H. S. Balyan (hsbalyan@gmail.com) (in exceptional case, bio-data may also be submitted at the time of interview) and attend the interview on Monday, March 30, 2015 at 11:00 AM in the Department of Genetics & Plant Breeding, Ch. Charan Singh University, Meerut. Candidates shall bring their original documents at the time of interview for verification. No interview letters will be issued and no TA/DA will be paid.