Microarray expression matrix platform GPL6106 and clinical data for 67 septicemic patients and made them available as GEO accession GSE13015. GSE13015 data have been parsed into a SummarizedExperiment object available in ExperimentHub can be used for Differential Expression Analysis, Modular repertiore analysis.
In the below example, we show how one can download this dataset from ExperimentHub.
library(ExperimentHub)## Loading required package: BiocGenerics##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
##
## Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
## as.data.frame, basename, cbind, colnames, dirname, do.call,
## duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
## lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
## pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
## tapply, union, unique, unsplit, which.max, which.min## Loading required package: AnnotationHub## Loading required package: BiocFileCache## Loading required package: dbplyrdat = ExperimentHub()
hub = query(dat , "GSE13015")
temp = hub[["EH5429"]]## see ?GSE13015 and browseVignettes('GSE13015') for documentation## loading from cache## require("SummarizedExperiment")sessionInfo()## R version 4.3.1 (2023-06-16)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.18-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## 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
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] SummarizedExperiment_1.32.0 GenomicRanges_1.54.0
## [3] GenomeInfoDb_1.38.0 IRanges_2.36.0
## [5] S4Vectors_0.40.0 MatrixGenerics_1.14.0
## [7] matrixStats_1.0.0 GSE13015_1.10.0
## [9] GEOquery_2.70.0 Biobase_2.62.0
## [11] ExperimentHub_2.10.0 AnnotationHub_3.10.0
## [13] BiocFileCache_2.10.0 dbplyr_2.3.4
## [15] BiocGenerics_0.48.0 BiocStyle_2.30.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.2.0 dplyr_1.1.3
## [3] blob_1.2.4 filelock_1.0.2
## [5] Biostrings_2.70.1 bitops_1.0-7
## [7] fastmap_1.1.1 RCurl_1.98-1.12
## [9] promises_1.2.1 digest_0.6.33
## [11] mime_0.12 lifecycle_1.0.3
## [13] ellipsis_0.3.2 statmod_1.5.0
## [15] KEGGREST_1.42.0 interactiveDisplayBase_1.40.0
## [17] RSQLite_2.3.1 magrittr_2.0.3
## [19] compiler_4.3.1 rlang_1.1.1
## [21] sass_0.4.7 tools_4.3.1
## [23] utf8_1.2.4 yaml_2.3.7
## [25] data.table_1.14.8 knitr_1.44
## [27] S4Arrays_1.2.0 bit_4.0.5
## [29] curl_5.1.0 DelayedArray_0.28.0
## [31] xml2_1.3.5 abind_1.4-5
## [33] withr_2.5.1 purrr_1.0.2
## [35] grid_4.3.1 preprocessCore_1.64.0
## [37] fansi_1.0.5 xtable_1.8-4
## [39] cli_3.6.1 rmarkdown_2.25
## [41] crayon_1.5.2 generics_0.1.3
## [43] httr_1.4.7 tzdb_0.4.0
## [45] DBI_1.1.3 cachem_1.0.8
## [47] zlibbioc_1.48.0 AnnotationDbi_1.64.0
## [49] BiocManager_1.30.22 XVector_0.42.0
## [51] vctrs_0.6.4 Matrix_1.6-1.1
## [53] jsonlite_1.8.7 bookdown_0.36
## [55] hms_1.1.3 bit64_4.0.5
## [57] limma_3.58.0 jquerylib_0.1.4
## [59] tidyr_1.3.0 glue_1.6.2
## [61] BiocVersion_3.18.0 later_1.3.1
## [63] tibble_3.2.1 pillar_1.9.0
## [65] rappdirs_0.3.3 htmltools_0.5.6.1
## [67] GenomeInfoDbData_1.2.11 R6_2.5.1
## [69] lattice_0.22-5 evaluate_0.22
## [71] shiny_1.7.5.1 readr_2.1.4
## [73] png_0.1-8 memoise_2.0.1
## [75] httpuv_1.6.12 bslib_0.5.1
## [77] Rcpp_1.0.11 SparseArray_1.2.0
## [79] xfun_0.40 pkgconfig_2.0.3