KRISHI
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/81535
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rahul Banerjee | en_US |
dc.contributor.author | Bharti | en_US |
dc.contributor.author | Shbana Begum | en_US |
dc.contributor.author | Pankaj Das | en_US |
dc.contributor.author | Tauqueer Ahmad | en_US |
dc.date.accessioned | 2024-03-01T15:19:55Z | - |
dc.date.available | 2024-03-01T15:19:55Z | - |
dc.date.issued | 2023-10-31 | - |
dc.identifier.citation | 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. | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/81535 | - |
dc.description | Not Available | en_US |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | Hindi | en_US |
dc.publisher | Bhartiya Krishi Anusandhan Patrika | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | BEAGLE | en_US |
dc.subject | fastPHASE | en_US |
dc.subject | Genome wide association studies | en_US |
dc.subject | Imputation methods | en_US |
dc.subject | IMPUTE | en_US |
dc.subject | MACH | en_US |
dc.subject | Missing mechanisms | en_US |
dc.title | Issues and Challenges of Imputation Techniques in Genome Wide Association Studies (GWAS): A Review | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Article | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Bhartiya Krishi Anusandhan Patrika | en_US |
dc.publication.volumeno | 38(3) | en_US |
dc.publication.pagenumber | 193-202 | en_US |
dc.publication.divisionUnit | Division of Sample Surveys | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.sourceUrl | https://arccjournals.com/journal/bhartiya-krishi-anusandhan-patrika/BKAP597 | en_US |
dc.publication.authorAffiliation | ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa-110 012, New Delhi, India | en_US |
dc.publication.authorAffiliation | ICAR-National Institute for Plant Biotechnology, LBS Centre, Pusa-110 012, New Delhi, India. | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | Not Available | en_US |
dc.publication.naasrating | 4.95 | en_US |
dc.publication.impactfactor | Not Available | en_US |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01 (193-202) BKAP597 (1).pdf | 486.84 kB | Adobe PDF | View/Open |
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