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, 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()## snapshotDate(): 2021-10-18hub = query(dat , "GSE13015")
temp = hub[["EH5429"]]## see ?GSE13015 and browseVignettes('GSE13015') for documentation## loading from cachesessionInfo()## R version 4.1.1 (2021-08-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.14-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.14-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] GSE13015_1.2.0 GEOquery_2.62.0 Biobase_2.54.0
## [4] ExperimentHub_2.2.0 AnnotationHub_3.2.0 BiocFileCache_2.2.0
## [7] dbplyr_2.1.1 BiocGenerics_0.40.0 BiocStyle_2.22.0
##
## loaded via a namespace (and not attached):
## [1] MatrixGenerics_1.6.0 httr_1.4.2
## [3] sass_0.4.0 tidyr_1.1.4
## [5] bit64_4.0.5 jsonlite_1.7.2
## [7] bslib_0.3.1 shiny_1.7.1
## [9] assertthat_0.2.1 interactiveDisplayBase_1.32.0
## [11] BiocManager_1.30.16 stats4_4.1.1
## [13] blob_1.2.2 GenomeInfoDbData_1.2.7
## [15] yaml_2.2.1 BiocVersion_3.14.0
## [17] lattice_0.20-45 pillar_1.6.4
## [19] RSQLite_2.2.8 glue_1.4.2
## [21] limma_3.50.0 digest_0.6.28
## [23] GenomicRanges_1.46.0 promises_1.2.0.1
## [25] XVector_0.34.0 Matrix_1.3-4
## [27] preprocessCore_1.56.0 htmltools_0.5.2
## [29] httpuv_1.6.3 pkgconfig_2.0.3
## [31] bookdown_0.24 zlibbioc_1.40.0
## [33] purrr_0.3.4 xtable_1.8-4
## [35] later_1.3.0 tzdb_0.2.0
## [37] tibble_3.1.5 KEGGREST_1.34.0
## [39] generics_0.1.1 IRanges_2.28.0
## [41] ellipsis_0.3.2 SummarizedExperiment_1.24.0
## [43] cachem_1.0.6 withr_2.4.2
## [45] magrittr_2.0.1 crayon_1.4.1
## [47] mime_0.12 memoise_2.0.0
## [49] evaluate_0.14 fansi_0.5.0
## [51] xml2_1.3.2 tools_4.1.1
## [53] data.table_1.14.2 hms_1.1.1
## [55] matrixStats_0.61.0 lifecycle_1.0.1
## [57] stringr_1.4.0 S4Vectors_0.32.0
## [59] DelayedArray_0.20.0 AnnotationDbi_1.56.1
## [61] Biostrings_2.62.0 compiler_4.1.1
## [63] jquerylib_0.1.4 GenomeInfoDb_1.30.0
## [65] rlang_0.4.12 grid_4.1.1
## [67] RCurl_1.98-1.5 rappdirs_0.3.3
## [69] bitops_1.0-7 rmarkdown_2.11
## [71] DBI_1.1.1 curl_4.3.2
## [73] R6_2.5.1 knitr_1.36
## [75] dplyr_1.0.7 fastmap_1.1.0
## [77] bit_4.0.4 utf8_1.2.2
## [79] filelock_1.0.2 readr_2.0.2
## [81] stringi_1.7.5 Rcpp_1.0.7
## [83] vctrs_0.3.8 png_0.1-7
## [85] tidyselect_1.1.1 xfun_0.27