cosihap

<p>A dataset containing 10,000 haplotypes of SNP sequences
mimicking the European population generated from the COSI software</p>

datasets


The explosion of biobank data offers immediate opportunities for
gene-environment (GxE) interaction studies of complex diseases because of the
large sample sizes and rich collection in genetic and non-genetic information.
However, the extremely large sample size also introduces new computational
challenges in GxE assessment, especially for set-based GxE variance component (VC)
tests, a widely used strategy to boost overall GxE signals and to evaluate the
joint GxE effect of multiple variants from a biologically meaningful unit
(e.g., gene).
We present 'SEAGLE', a Scalable Exact AlGorithm for Large-scale Set-based
GxE tests, to permit GxE VC test scalable to biobank data. 'SEAGLE' employs modern
matrix computations to achieve the same <e2><80><9c>exact<e2><80><9d> results as the original GxE VC
tests, and does not impose additional assumptions nor relies on approximations.
'SEAGLE' can easily accommodate sample sizes in the order of 10^5, is implementable
on standard laptops, and does not require specialized equipment.
The accompanying manuscript for this package can be found at Chi, Ipsen, Hsiao,
Lin, Wang, Lee, Lu, and Tzeng. (2021+) <arXiv:2105.03228>.

Jocelyn Chi

SEAGLE

Scalable Exact Algorithm for Large-Scale Set-Based
Gene-Environment Interaction Tests

Ilse Ipsen

Jung-Ying Tzeng

cosihap function

<p>An object of class <code>dgCMatrix</code> with 10000 rows and 604 columns.</p>

cosihap: Synthetic haplotype data generated from COSI software

Description

Usage

Arguments

Format