Bioinformatics Analyst

Bioinformatics Analyst Interview Questions and Answers

Updated 2 Jun 2023

Q1. What databases are used for population genetics

Ans.

Various databases are used for population genetics research, including dbSNP, 1000 Genomes Project, and HapMap.

dbSNP: a database of single nucleotide polymorphisms (SNPs) maintained by the National Center for Biotechnology Information (NCBI)
1000 Genomes Project: a public database of genetic variation in over 2,500 individuals from 26 populations worldwide
HapMap: a database of common genetic variations in human populations, used to identify genetic factors associated with dise...read more

Ans.

I am familiar with various file formats used in bioinformatics.

Ans.

I am familiar with various databases including GenBank, UniProt, NCBI, and PDB.

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NGS pipeline involves steps like quality control, alignment, variant calling, annotation, and interpretation.

Quality control of raw data to remove low-quality reads and adapters
Alignment of reads to a reference genome or transcriptome
Variant calling to identify genetic variations
Annotation of variants to determine their functional impact
Interpretation of results to draw conclusions about the biological significance of the variants
Examples of tools used in NGS pipeline are Fas...read more

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Ans.

Sequencing is the process of determining the order of nucleotides in a DNA or RNA molecule.

DNA or RNA is extracted from the sample
The DNA or RNA is fragmented into smaller pieces
The fragments are amplified through PCR
The amplified fragments are sequenced using various methods such as Sanger sequencing or Next-Generation Sequencing (NGS)
The resulting sequence data is analyzed and assembled to generate the final sequence

Ans.

NGS data analysis involves processing and interpreting large amounts of sequencing data to extract meaningful biological insights.

NGS data analysis involves quality control, alignment, variant calling, and downstream analysis.
Tools like BWA, GATK, and SAMtools are commonly used for NGS data analysis.
Common analyses include identifying genetic variants, gene expression levels, and pathway analysis.
NGS data analysis can be used in genomics, transcriptomics, epigenomics, and met...read more

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