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Here, the C in the reference genome has been replaced by a T in the variant.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

Walk-in-Interview will be held on 04th March 2015 at 11.30 A.M. in the Bio- Informatics Centre of Bose Institute, P-1/12, C.I.T. Scheme VII-M, Kolkata- 700054 for two (02) positions of Research Associate/ Extended Senior Research Fellow in the DBT sponsored following two projects running under the CoE- Bioinformatics under the guidance of Prof. Pinakpani Chakrabarti, Bioinformatics Centre.

Position : RA/SRF
Project title : 1. "Centre of Excellence (CoE) in Bioinformatics at Bose Institute”,2. Project entitled “Setting up of National Facility on Interactive Graphysics Computer System (IGCS) for Biomolecular Modeling, Molecular Dynamics & Structures”

Desired Profile : Ph.D degree in Biological or Chemical Sciences with in-depth understanding of protein structure and dynamics for R.A. position.Those who have submitted thesis can be considered for Extended SRF position
Preferred : Knowledge of computer programming and bioinformatics softwares.
Stipend : For R.A- Rs. 22,000/- p.m., plus admissible H.R.A. and Medical benefit. For Extended SRF - Rs. 20,000/- p.m., plus admissible H.R.A.and Medical benefit.
Age : For R.A- Below 35 years; For Extended SRF - Below 33 years
Interested and eligible candidates should appear before the Selection Committee with atyped application addressed to the Sr.Prof. & In-Charge, Registrar's Office, Bose Institute, P- 1/12, CIT Scheme VII-M, Kankurgachi, Kolkata-700054 along with Bio-data giving details of qualification i.e. examination passed, year, division, percentage of marks from Secondary onwards with attested copies of Certificates, Mark-Sheet and testimonials. The candidates should also bring the original mark-sheets, certificates etc. at the time of Interview.

Walk in Interview : 04.03.15

More at http://www.boseinst.ernet.in/ADVT/14/p_34.pdf

Research Associate Biotechnology /JRF / Lab. Assistant recruitment in Indian Institute of Vegetable Research

Project:
Genomics assisted selection of Solanum chilense introgression lines for enhancing drought tolerance in tomato
Post Name : Research Associate
Qualification : Ph.D in Biotechnology/ Bioinformatics/Genetics & Plant Breeding. M. Tech in Computer Science with at least one research paper in science citation indexed journal. Desirable: Experience in bioinformatics and next generation sequence data handling. Familiarity in Linux, R, Perl/Phython or other programming languages. Willingness to travel to European partner centers.

Pay Scale : Rs. 36000 for 1st and 2nd year as per rules for Research Associate. Rs. 25000/- for 1st and 2nd year and Rs. 28000 as per rules for Junior Research Fellow. Rs. 7000/- for Lab. Assistant.

Age : Not more than 35 years for Men and 40 years for Women (Relaxable for SC/ST/OBC/PH candidates as per rules) for Research Associate/ Junior Research Fellow. Minimum age will be 21 years and maximum age will be 45 years (Relaxable for SC/ST/OBC/PH candidates as per rules) for Lab.Assistant.

More at http://iivr.org.in/Job%20Oppurtunities/RA20.03.2015.pdf

Human genetic variation
Inference of human evolutionary history from genetic markers
Statistical analysis of population-genetic data
Mathematical models of gene genealogies
Theoretical population genetics
Combinatorics of evolutionary trees
The relationship between gene trees and species trees
The role of human evolutionary genetics in the search for genes that contribute to disease-susceptibility
More at https://web.stanford.edu/group/rosenberglab/index.html