piano
piano 2.14.0
library(piano)
data("gsa_input")
head(gsa_input$gsc,10)
## g s
## [1,] "g103" "s1"
## [2,] "g106" "s19"
## [3,] "g118" "s16"
## [4,] "g130" "s21"
## [5,] "g130" "s6"
## [6,] "g131" "s46"
## [7,] "g132" "s32"
## [8,] "g132" "s3"
## [9,] "g139" "s1"
## [10,] "g140" "s21"
head(gsa_input$pvals, 10)
## g1 g2 g3 g4 g5 g6
## 2.351900e-05 2.838832e-05 2.885141e-05 6.566243e-05 7.107615e-05 7.770070e-05
## g7 g8 g9 g10
## 1.436830e-04 1.532264e-04 1.626607e-04 1.644806e-04
head(gsa_input$directions, 10)
## g1 g2 g3 g4 g5 g6 g7 g8 g9 g10
## -1 -1 1 -1 -1 1 -1 -1 -1 -1
geneSets <- loadGSC(gsa_input$gsc)
geneSets
## First 50 (out of 50) gene set names:
## [1] "s1" "s19" "s16" "s21" "s6" "s46" "s32" "s3" "s34" "s14" "s7" "s13"
## [13] "s5" "s42" "s2" "s11" "s22" "s8" "s15" "s10" "s33" "s37" "s35" "s43"
## [25] "s36" "s27" "s17" "s9" "s23" "s30" "s18" "s25" "s41" "s24" "s20" "s39"
## [37] "s31" "s12" "s29" "s4" "s26" "s44" "s28" "s47" "s38" "s49" "s50" "s40"
## [49] "s45" "s48"
##
## First 50 (out of 1136) gene names:
## [1] "g103" "g139" "g150" "g235" "g304" "g479" "g130" "g157" "g171" "g180"
## [11] "g218" "g243" "g251" "g302" "g319" "g32" "g329" "g372" "g373" "g403"
## [21] "g41" "g43" "g456" "g476" "g48" "g521" "g527" "g554" "g581" "g585"
## [31] "g591" "g62" "g660" "g665" "g698" "g71" "g711" "g723" "g726" "g75"
## [41] "g758" "g77" "g808" "g816" "g838" "g9" "g907" "g924" "g931" "g935"
##
## Gene set size summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.00 20.50 39.00 39.50 53.75 95.00
##
## No additional info available.
gsares <- runGSA(gsa_input$pvals,
gsa_input$directions,
gsc = geneSets,
nPerm = 500) # set to 500 for fast run
Note: nPerm
was set to 500 to get a short runtime for this vignette, in reality use a higher number, e.g. 10,000 (default).
exploreGSAres(gsares)
This opens a browser window with an interactive interface where the results can be explored in detail.
Here is the output of sessionInfo()
on the system on which this document was compiled.
## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] piano_2.14.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] Biobase_2.58.0 sass_0.4.2 jsonlite_1.8.3
## [4] gtools_3.9.3 bslib_0.4.0 shiny_1.7.3
## [7] assertthat_0.2.1 BiocManager_1.30.19 yaml_2.3.6
## [10] slam_0.1-50 pillar_1.8.1 lattice_0.20-45
## [13] glue_1.6.2 limma_3.54.0 digest_0.6.30
## [16] promises_1.2.0.1 colorspace_2.0-3 cowplot_1.1.1
## [19] htmltools_0.5.3 httpuv_1.6.6 Matrix_1.5-1
## [22] pkgconfig_2.0.3 bookdown_0.29 xtable_1.8-4
## [25] relations_0.6-12 scales_1.2.1 later_1.3.0
## [28] BiocParallel_1.32.0 tibble_3.1.8 generics_0.1.3
## [31] ggplot2_3.3.6 ellipsis_0.3.2 DT_0.26
## [34] cachem_1.0.6 shinyjs_2.1.0 BiocGenerics_0.44.0
## [37] cli_3.4.1 magrittr_2.0.3 mime_0.12
## [40] evaluate_0.17 fansi_1.0.3 gplots_3.1.3
## [43] shinydashboard_0.7.2 tools_4.2.1 data.table_1.14.4
## [46] lifecycle_1.0.3 stringr_1.4.1 munsell_0.5.0
## [49] cluster_2.1.4 compiler_4.2.1 jquerylib_0.1.4
## [52] caTools_1.18.2 rlang_1.0.6 grid_4.2.1
## [55] marray_1.76.0 htmlwidgets_1.5.4 visNetwork_2.1.2
## [58] igraph_1.3.5 bitops_1.0-7 rmarkdown_2.17
## [61] gtable_0.3.1 codetools_0.2-18 DBI_1.1.3
## [64] sets_1.0-21 R6_2.5.1 knitr_1.40
## [67] dplyr_1.0.10 fastmap_1.1.0 utf8_1.2.2
## [70] fastmatch_1.1-3 fgsea_1.24.0 KernSmooth_2.23-20
## [73] stringi_1.7.8 parallel_4.2.1 Rcpp_1.0.9
## [76] vctrs_0.5.0 tidyselect_1.2.0 xfun_0.34