SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration

被引：5

作者：

Matushyn, Mykyta ^{[1
]}

Bose, Madhuchanda ^{[1
]}

Mahmoud, Abdallah Amr ^{[1
]}

Cuthbertson, Lewis ^{[1
]}

Tello, Carlos ^{[1
]}

Bircan, Karatug Ozan ^{[1
]}

Terpolovsky, Andrew ^{[1
]}

Bamunusinghe, Varuna ^{[1
]}

Khan, Umar ^{[1
]}

Novkovic, Biljana ^{[1
]}

Grabherr, Manfred G. ^{[1
]}

Yazdi, Puya G. ^{[1
]}

机构：

[1] SelfDecode Com, 1031 Ives Dairy Rd Suite 228-1047, Miami, FL 33179 USA

来源：

BMC BIOINFORMATICS | 2022年 / 23卷 / 01期

关键词：

Bioinformatics; GWAS; Summary statistics; PRS; Genetics; GENOME-WIDE ASSOCIATION;

D O I：

10.1186/s12859-022-04920-7

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Background Generating polygenic risk scores for diseases and complex traits requires high quality GWAS summary statistic files. Often, these files can be difficult to acquire either as a result of unshared or incomplete data. To date, bioinformatics tools which focus on restoring missing columns containing identification and association data are limited, which has the potential to increase the number of usable GWAS summary statistics files. Results SumStatsRehab was able to restore rsID, effect/other alleles, chromosome, base pair position, effect allele frequencies, beta, standard error, and p-values to a better extent than any other currently available tool, with minimal loss. Conclusions SumStatsRehab offers a unique tool utilizing both functional programming and pipeline-like architecture, allowing users to generate accurate data restorations for incomplete summary statistics files. This in turn, increases the number of usable GWAS summary statistics files, which may be invaluable for less researched health traits.

引用

页数：12

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