mgcca_hdf5: Generalized canonical correlation with missing individuals...

In isglobal-brge/GCCA: Generalized Canonical Correlation Analysis having missing individuals

Description

Generalized canonical correlation with missing individuals for big data

Usage

mgcca_hdf5(
  x,
  datanames,
  nfac = 2,
  scale = TRUE,
  pval = TRUE,
  scores = FALSE,
  method = "solve",
  lambda,
  mc.cores = 1,
  ...
)

Arguments

x	string for hdf5 file where data to process will be under MGCCA_IN group . Results will be stored in the same data file under MGCCA_OUT group. Missing is not allowed (see details).
datanames	string array with datasetnames to use with mcgga
nfac	...
scale	...
pval	should p-values of correlation between variables and shared canonical variates be computed? Default is TRUE.
scores	should canonical variables be computed for each table? Default is FALSE. See details
method	...
lambda	...
mc.cores	...

Details

NOT WORKING

Value

a list consisting of

Y	canonical components for the shared space
corsY	correlation between variables and shared canonical components
scores	canonical componets for each table
p.values	p-values of correlation between variables and shared canonical components
AVE	indicators of model quality based on the Average Variance Explained (AVE): AVE for each table, AVE_outer (average accross tables), AVE_inner(for the shared component).

Examples

see vignette

isglobal-brge/GCCA documentation built on Feb. 19, 2022, 9:21 a.m.