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, 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 4.4.0 beta (2024-04-15 r86425)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.19-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_1.34.0 GenomicRanges_1.56.0
## [3] GenomeInfoDb_1.40.0 IRanges_2.38.0
## [5] S4Vectors_0.42.0 MatrixGenerics_1.16.0
## [7] matrixStats_1.3.0 GSE13015_1.12.0
## [9] GEOquery_2.72.0 Biobase_2.64.0
## [11] ExperimentHub_2.12.0 AnnotationHub_3.12.0
## [13] BiocFileCache_2.12.0 dbplyr_2.5.0
## [15] BiocGenerics_0.50.0 BiocStyle_2.32.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.2.1 dplyr_1.1.4 blob_1.2.4
## [4] filelock_1.0.3 Biostrings_2.72.0 fastmap_1.1.1
## [7] digest_0.6.35 mime_0.12 lifecycle_1.0.4
## [10] statmod_1.5.0 KEGGREST_1.44.0 RSQLite_2.3.6
## [13] magrittr_2.0.3 compiler_4.4.0 rlang_1.1.3
## [16] sass_0.4.9 tools_4.4.0 utf8_1.2.4
## [19] yaml_2.3.8 data.table_1.15.4 knitr_1.46
## [22] S4Arrays_1.4.0 bit_4.0.5 curl_5.2.1
## [25] DelayedArray_0.30.0 xml2_1.3.6 abind_1.4-5
## [28] withr_3.0.0 purrr_1.0.2 grid_4.4.0
## [31] preprocessCore_1.66.0 fansi_1.0.6 cli_3.6.2
## [34] rmarkdown_2.26 crayon_1.5.2 generics_0.1.3
## [37] httr_1.4.7 tzdb_0.4.0 DBI_1.2.2
## [40] cachem_1.0.8 zlibbioc_1.50.0 AnnotationDbi_1.66.0
## [43] BiocManager_1.30.22 XVector_0.44.0 vctrs_0.6.5
## [46] Matrix_1.7-0 jsonlite_1.8.8 bookdown_0.39
## [49] hms_1.1.3 bit64_4.0.5 limma_3.60.0
## [52] jquerylib_0.1.4 tidyr_1.3.1 glue_1.7.0
## [55] BiocVersion_3.19.1 UCSC.utils_1.0.0 tibble_3.2.1
## [58] pillar_1.9.0 rappdirs_0.3.3 htmltools_0.5.8.1
## [61] GenomeInfoDbData_1.2.12 R6_2.5.1 evaluate_0.23
## [64] lattice_0.22-6 readr_2.1.5 png_0.1-8
## [67] memoise_2.0.1 bslib_0.7.0 SparseArray_1.4.0
## [70] xfun_0.43 pkgconfig_2.0.3