An Introduction to the GSDA Package

The GSDA package (short for Gene-set Distance Analysis) contains functions to to carry out the gene-set distance analysis (GSDA) by generalizing distance correlations to evaluate the association of a gene set with categorical, quantitative, and censored event-time variables. GSDA loads packages as needed and assumes that they are installed.

An example to run GSDA on target aml RNAseq with Chloroma status (categorical) with myeloid gene sets defined by kegg.

chl.res=gsda(sqrt(target.aml.expr),
             target.aml.clin,
             kegg.ml.gsets,
             "Chloroma","oe","ct")
chl.res
#>                            vset   dCor p.vset
#> 1   KEGG_ACUTE_MYELOID_LEUKEMIA 0.0271 0.0201
#> 2 KEGG_CHRONIC_MYELOID_LEUKEMIA 0.0181 0.1193
#>   comp.time
#> 1     0.009
#> 2     0.012

An example to run GSDA on target aml RNAseq with White blood counts (quantitative) with myeloid gene sets defined by kegg.

wbc.res=gsda(sqrt(target.aml.expr),
             target.aml.clin,
             kegg.ml.gsets,
             "logWBC","oe","oe")
wbc.res
#>                            vset  dCor   p.vset
#> 1   KEGG_ACUTE_MYELOID_LEUKEMIA 0.132 6.98e-30
#> 2 KEGG_CHRONIC_MYELOID_LEUKEMIA 0.073 3.43e-10
#>   comp.time
#> 1     0.003
#> 2     0.004

An example to run GSDA on target aml RNAseq with event free survival (efs, censored event-time) with myeloid gene sets defined by kegg.

efs.res=gsda(sqrt(target.aml.expr),
             target.aml.clin,
             kegg.ml.gsets,
             c("efs.time","efs.evnt"),"oe","st")
efs.res
#>                            vset    dCor p.vset
#> 1   KEGG_ACUTE_MYELOID_LEUKEMIA 0.02186 0.0604
#> 2 KEGG_CHRONIC_MYELOID_LEUKEMIA 0.00163 0.8888
#>   comp.time
#> 1     0.019
#> 2     0.020
options(old)

Install GSDA using

devtools::install_github('xueyuancao/GSDA', dependencies = c("Depends", "Suggests"))