Gene set results
Usage
geneSetResults(object, ...)
# S4 method for FgseaList
geneSetResults(object, contrast, collection, set)Arguments
- object
Object.
- contrast
character(1). Contrast name.- collection
character(1). Gene set collection name. Typically refers toh(hallmark),c1-c7collections from MSigDb. Can obtain usingcollectionNames()onFgseaListobject.- set
character(1). Gene set name, in a definedcollection. For example,"HALLMARK_ADIPOGENESIS".- ...
Additional arguments.
Examples
data(fgsea)
## FgseaList ====
object <- fgsea
contrast <- contrastNames(object)[[1L]]
collection <- collectionNames(object)[[1L]]
set <- geneSetNames(object = object, collection = collection)[[1L]]
geneSetResults(
object = object,
contrast = contrast,
collection = collection,
set = set
)
#> log2 fold change (MLE): condition B vs A
#> Wald test p-value: condition B vs A
#> DataFrame with 12 rows and 20 columns
#> baseMean log2FoldChange lfcSE stat pvalue
#> <numeric> <numeric> <numeric> <numeric> <numeric>
#> ENSG00000065833 13.39195 1.647967 0.877714 1.877566 0.0604405
#> ENSG00000062485 2.98718 1.470322 2.029788 0.724372 0.4688372
#> ENSG00000011566 21.76059 0.393937 0.676277 0.582509 0.5602241
#> ENSG00000004455 6.95828 0.647314 1.352942 0.478450 0.6323303
#> ENSG00000019144 14.23372 0.369988 0.817018 0.452852 0.6506556
#> ... ... ... ... ... ...
#> ENSG00000042445 2.71417 -0.468907 1.389382 -0.337493 0.735745
#> ENSG00000010256 13.03512 -0.348417 0.795043 -0.438236 0.661215
#> ENSG00000065534 90.46881 -0.218196 0.402197 -0.542511 0.587467
#> ENSG00000004779 41.14449 -0.738746 0.491476 -1.503116 0.132809
#> ENSG00000006831 45.86941 -0.867888 0.539842 -1.607669 0.107908
#> padj geneId geneName sample1 sample2
#> <numeric> <character> <character> <numeric> <numeric>
#> ENSG00000065833 0.900794 ENSG00000065833 ME1 5.865349 5.73587
#> ENSG00000062485 0.994236 ENSG00000062485 CS 0.977558 0.00000
#> ENSG00000011566 0.994236 ENSG00000011566 MAP4K3 23.461395 21.03153
#> ENSG00000004455 0.994236 ENSG00000004455 AK2 2.932674 12.42772
#> ENSG00000019144 0.994236 ENSG00000019144 PHLDB1 19.551162 14.33968
#> ... ... ... ... ... ...
#> ENSG00000042445 0.994236 ENSG00000042445 RETSAT 5.86535 2.86794
#> ENSG00000010256 0.994236 ENSG00000010256 UQCRC1 7.82046 13.38370
#> ENSG00000065534 0.994236 ENSG00000065534 MYLK 93.84558 105.15765
#> ENSG00000004779 0.900794 ENSG00000004779 NDUFAB1 43.01256 68.83046
#> ENSG00000006831 0.900794 ENSG00000006831 ADIPOR2 58.65349 35.37121
#> sample3 sample4 sample5 sample6 sample7 sample8
#> <numeric> <numeric> <numeric> <numeric> <numeric> <numeric>
#> ENSG00000065833 1.95673 32.14264 16.47367 13.79947 13.4696 3.83823
#> ENSG00000062485 0.00000 0.00000 10.06724 4.92838 0.0000 1.91911
#> ENSG00000011566 6.84854 12.28983 4.57602 24.64191 36.5602 11.51468
#> ENSG00000004455 0.00000 15.12595 0.00000 7.88541 19.2422 0.00000
#> ENSG00000019144 21.52399 1.89074 8.23684 4.92838 8.6590 9.59557
#> ... ... ... ... ... ... ...
#> ENSG00000042445 1.95673 4.72686 1.83041 0.985677 1.92422 1.91911
#> ENSG00000010256 20.54563 14.18057 8.23684 36.470033 14.43167 6.71690
#> ENSG00000065534 96.85798 59.55841 34.77775 102.510362 84.66582 99.79393
#> ENSG00000004779 21.52399 41.59635 67.72509 55.197887 23.09068 34.54405
#> ENSG00000006831 104.68488 41.59635 28.37132 87.725213 41.37080 40.30140
#> sample9 sample10 sample11 sample12
#> <numeric> <numeric> <numeric> <numeric>
#> ENSG00000065833 25.230324 3.74870 25.17695 13.26586
#> ENSG00000062485 0.970397 12.18326 2.90503 1.89512
#> ENSG00000011566 19.407942 28.11522 30.98701 41.69272
#> ENSG00000004455 4.851985 3.74870 10.65178 6.63293
#> ENSG00000019144 53.371839 8.43457 17.43019 2.84269
#> ... ... ... ... ...
#> ENSG00000042445 3.88159 1.87435 0.0000 4.73781
#> ENSG00000010256 11.64476 1.87435 12.5885 8.52806
#> ENSG00000065534 69.86859 92.78024 106.5178 139.29157
#> ENSG00000004779 22.31913 43.11001 35.8287 36.95491
#> ENSG00000006831 27.17112 42.17284 17.4302 25.58417