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## Loading required package: parallel##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:parallel':
##
## clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
## clusterExport, clusterMap, parApply, parCapply, parLapply,
## parLapplyLB, parRapply, parSapply, parSapplyLB## 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(): 2021-05-05hub = query(dat , "GSE13015")
temp = hub[["EH5429"]]## see ?GSE13015 and browseVignettes('GSE13015') for documentation## loading from cachesessionInfo()## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.13-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 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] parallel stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] GSE13015_1.0.0 GEOquery_2.60.0 Biobase_2.52.0
## [4] ExperimentHub_2.0.0 AnnotationHub_3.0.0 BiocFileCache_2.0.0
## [7] dbplyr_2.1.1 BiocGenerics_0.38.0 BiocStyle_2.20.0
##
## loaded via a namespace (and not attached):
## [1] MatrixGenerics_1.4.0 httr_1.4.2
## [3] sass_0.4.0 tidyr_1.1.3
## [5] bit64_4.0.5 jsonlite_1.7.2
## [7] bslib_0.2.5.1 shiny_1.6.0
## [9] assertthat_0.2.1 interactiveDisplayBase_1.30.0
## [11] BiocManager_1.30.15 stats4_4.1.0
## [13] blob_1.2.1 GenomeInfoDbData_1.2.6
## [15] yaml_2.2.1 BiocVersion_3.13.1
## [17] lattice_0.20-44 pillar_1.6.1
## [19] RSQLite_2.2.7 glue_1.4.2
## [21] limma_3.48.0 digest_0.6.27
## [23] GenomicRanges_1.44.0 promises_1.2.0.1
## [25] XVector_0.32.0 Matrix_1.3-3
## [27] htmltools_0.5.1.1 httpuv_1.6.1
## [29] preprocessCore_1.54.0 pkgconfig_2.0.3
## [31] bookdown_0.22 zlibbioc_1.38.0
## [33] purrr_0.3.4 xtable_1.8-4
## [35] later_1.2.0 tibble_3.1.2
## [37] KEGGREST_1.32.0 generics_0.1.0
## [39] IRanges_2.26.0 ellipsis_0.3.2
## [41] SummarizedExperiment_1.22.0 cachem_1.0.5
## [43] withr_2.4.2 magrittr_2.0.1
## [45] crayon_1.4.1 mime_0.10
## [47] memoise_2.0.0 evaluate_0.14
## [49] fansi_0.4.2 xml2_1.3.2
## [51] tools_4.1.0 hms_1.1.0
## [53] matrixStats_0.58.0 lifecycle_1.0.0
## [55] stringr_1.4.0 S4Vectors_0.30.0
## [57] DelayedArray_0.18.0 AnnotationDbi_1.54.0
## [59] Biostrings_2.60.0 compiler_4.1.0
## [61] jquerylib_0.1.4 GenomeInfoDb_1.28.0
## [63] rlang_0.4.11 grid_4.1.0
## [65] RCurl_1.98-1.3 rappdirs_0.3.3
## [67] bitops_1.0-7 rmarkdown_2.8
## [69] DBI_1.1.1 curl_4.3.1
## [71] R6_2.5.0 knitr_1.33
## [73] dplyr_1.0.6 fastmap_1.1.0
## [75] bit_4.0.4 utf8_1.2.1
## [77] filelock_1.0.2 readr_1.4.0
## [79] stringi_1.6.2 Rcpp_1.0.6
## [81] vctrs_0.3.8 png_0.1-7
## [83] tidyselect_1.1.1 xfun_0.23