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()## snapshotDate(): 2022-10-24hub = query(dat , "GSE13015")
temp = hub[["EH5429"]]## see ?GSE13015 and browseVignettes('GSE13015') for documentation## loading from cache## require("SummarizedExperiment")sessionInfo()## 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] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] SummarizedExperiment_1.28.0 GenomicRanges_1.50.0
## [3] GenomeInfoDb_1.34.0 IRanges_2.32.0
## [5] S4Vectors_0.36.0 MatrixGenerics_1.10.0
## [7] matrixStats_0.62.0 GSE13015_1.6.0
## [9] GEOquery_2.66.0 Biobase_2.58.0
## [11] ExperimentHub_2.6.0 AnnotationHub_3.6.0
## [13] BiocFileCache_2.6.0 dbplyr_2.2.1
## [15] BiocGenerics_0.44.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.4 sass_0.4.2
## [3] tidyr_1.2.1 bit64_4.0.5
## [5] jsonlite_1.8.3 bslib_0.4.0
## [7] shiny_1.7.3 assertthat_0.2.1
## [9] interactiveDisplayBase_1.36.0 BiocManager_1.30.19
## [11] blob_1.2.3 GenomeInfoDbData_1.2.9
## [13] yaml_2.3.6 BiocVersion_3.16.0
## [15] lattice_0.20-45 pillar_1.8.1
## [17] RSQLite_2.2.18 glue_1.6.2
## [19] limma_3.54.0 digest_0.6.30
## [21] promises_1.2.0.1 XVector_0.38.0
## [23] Matrix_1.5-1 preprocessCore_1.60.0
## [25] htmltools_0.5.3 httpuv_1.6.6
## [27] pkgconfig_2.0.3 bookdown_0.29
## [29] zlibbioc_1.44.0 purrr_0.3.5
## [31] xtable_1.8-4 later_1.3.0
## [33] tzdb_0.3.0 tibble_3.1.8
## [35] KEGGREST_1.38.0 generics_0.1.3
## [37] ellipsis_0.3.2 cachem_1.0.6
## [39] withr_2.5.0 cli_3.4.1
## [41] magrittr_2.0.3 crayon_1.5.2
## [43] mime_0.12 memoise_2.0.1
## [45] evaluate_0.17 fansi_1.0.3
## [47] xml2_1.3.3 tools_4.2.1
## [49] data.table_1.14.4 hms_1.1.2
## [51] lifecycle_1.0.3 stringr_1.4.1
## [53] DelayedArray_0.24.0 AnnotationDbi_1.60.0
## [55] Biostrings_2.66.0 compiler_4.2.1
## [57] jquerylib_0.1.4 rlang_1.0.6
## [59] grid_4.2.1 RCurl_1.98-1.9
## [61] rappdirs_0.3.3 bitops_1.0-7
## [63] rmarkdown_2.17 DBI_1.1.3
## [65] curl_4.3.3 R6_2.5.1
## [67] knitr_1.40 dplyr_1.0.10
## [69] fastmap_1.1.0 bit_4.0.4
## [71] utf8_1.2.2 filelock_1.0.2
## [73] readr_2.1.3 stringi_1.7.8
## [75] Rcpp_1.0.9 vctrs_0.5.0
## [77] png_0.1-7 tidyselect_1.2.0
## [79] xfun_0.34