Maximal Segmental Score Method for Localizing Recessive Disease Variants Based on Sequence Data.
ALSPAC
autosomal recessive disease
maximal segmental score
rare disease
whole-genome sequencing
Journal
Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621
Informations de publication
Date de publication:
2020
2020
Historique:
received:
30
01
2020
accepted:
07
05
2020
entrez:
14
7
2020
pubmed:
14
7
2020
medline:
14
7
2020
Statut:
epublish
Résumé
Due to the affordability of whole-genome sequencing, the genetic association design can now address rare diseases. However, some common statistical association methods only consider homozygosity mapping and need several criteria, such as sliding windows of a given size and statistical significance threshold setting, such as Our region-specific method, called expanded maximal segmental score (eMSS), converts Our simulation results show that eMSS had higher power as the number of non-causal haplotype blocks decreased. The type I error for eMSS under different scenarios was well controlled, When compared to HDR-del, our eMSS is powerful in analyzing even small numbers of recessive cases, and the results show that the method can further reduce numbers of candidate variants to a very small set of susceptibility pathogenic variants underlying OI and MIA. When we conduct whole-genome sequence analysis, eMSS used 3/5 the computation time of HDR-del. Without additional parameters needing to be set in the segment detection, the computational burden for eMSS is lower compared with that in other region-specific approaches.
Sections du résumé
BACKGROUND
BACKGROUND
Due to the affordability of whole-genome sequencing, the genetic association design can now address rare diseases. However, some common statistical association methods only consider homozygosity mapping and need several criteria, such as sliding windows of a given size and statistical significance threshold setting, such as
METHODS
METHODS
Our region-specific method, called expanded maximal segmental score (eMSS), converts
RESULTS
RESULTS
Our simulation results show that eMSS had higher power as the number of non-causal haplotype blocks decreased. The type I error for eMSS under different scenarios was well controlled,
CONCLUSIONS
CONCLUSIONS
When compared to HDR-del, our eMSS is powerful in analyzing even small numbers of recessive cases, and the results show that the method can further reduce numbers of candidate variants to a very small set of susceptibility pathogenic variants underlying OI and MIA. When we conduct whole-genome sequence analysis, eMSS used 3/5 the computation time of HDR-del. Without additional parameters needing to be set in the segment detection, the computational burden for eMSS is lower compared with that in other region-specific approaches.
Identifiants
pubmed: 32655614
doi: 10.3389/fgene.2020.00555
pmc: PMC7325894
doi:
Types de publication
Journal Article
Langues
eng
Pagination
555Subventions
Organisme : Medical Research Council
ID : MC_PC_15018
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_19009
Pays : United Kingdom
Informations de copyright
Copyright © 2020 Hsieh, Sie, Chang, Ott, Lian and Fann.
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