Issues and Challenges of Imputation Techniques in Genome Wide Association Studies (GWAS): A Review
KRISHI: Publication and Data Inventory Repository
View Archive InfoField | Value | |
Title |
Issues and Challenges of Imputation Techniques in Genome Wide Association Studies (GWAS): A Review
Not Available |
|
Creator |
Rahul Banerjee
Bharti Shbana Begum Pankaj Das Tauqueer Ahmad |
|
Subject |
BEAGLE
fastPHASE Genome wide association studies Imputation methods IMPUTE MACH Missing mechanisms |
|
Description |
Not Available
A genome-wide association study (GWAS) rapidly scans DNA markers in many individuals to find genetic links to diseases. New findings aid in disease detection, treatment and prevention. Imputation predicts untyped genotypes in genetic studies when data is missing due to quality, cost, or design issues. It’s a proven statistical technique for estimating unobserved genotypes by borrowing haplotype segments from a densely genotyped reference panel. This allows estimation and testing of associations at unassayed variants. Genotype imputation is vital in analyzing genome-wide association scans, helping geneticists evaluate evidence for association at untyped genetic markers. This summary outlines missing data issues and various imputation methods. Not Available |
|
Date |
2024-03-01T15:19:55Z
2024-03-01T15:19:55Z 2023-10-31 |
|
Type |
Article
|
|
Identifier |
Banerjee, R., Bharti, Begum, S., Das, P. and Ahmad, T. (2023). Issues and Challenges of Imputation Techniques in Genome Wide Association Studies (GWAS): A Review. Bhartiya Krishi Anusandhan Patrika. 38(3): 193-202. doi: 10.18805/BKAP597.
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/81535 |
|
Language |
Hindi
|
|
Relation |
Not Available;
|
|
Publisher |
Bhartiya Krishi Anusandhan Patrika
|
|