This package contains a SummarizedExperiment from the Yu et al. (2013) paper that performed the rat BodyMap across 11 organs and 4 developmental stages. Raw FASTQ files were downloaded and mapped using STAR. Data is available on ExperimentHub as a data package.
bodymapRat 1.24.0
The bodymapRat package contains gene expression
data on 652 RNA-Seq samples from a comprehensive rat
transcriptomic BodyMap study. These samples include
the sequence identifier information provided in the
header of the FASTQ files which can be used as a
surrogate for batch. These samples have not been
normalized or pre-processed.
The data are provided in a SummarizedExperiment. The
phenotypic information can be extracted using the
colData() function and a description of the phenotypic
data is listed in the table below:
| Title | Description |
|---|---|
| sraExperiment | SRA Experiment ID |
| title | Title of sample provided by the authors |
| geoAccession | GEO Accession ID |
| BioSample | BioSample ID |
| avgLength | Average read length |
| instrument | Machine identifier (from FASTQ header) |
| runID | Run ID (from FASTQ header) |
| fcID | Flow cell ID (from FASTQ header) |
| fcLane | Flow cell lane (from FASTQ header) |
| tile | Tile (from FASTQ header) |
| xtile | xtile (from FASTQ header) |
| ytile | ytile (from FASTQ header) |
| organ | Body organ |
| sex | Gender |
| stage | Stage |
| techRep | Technical replicate number |
| colOrgan | Column of colors to help with plotting |
| rnaRIN | RIN number |
| barcode | barcode number |
The data can be accessed as follows:
library(SummarizedExperiment)
library(bodymapRat)We use the bodymapRat() function to download the
relevant files from Bioconductor’s
ExperimentHub web
resource. Running this function will download a
SummarizedExperiment object, which contains read counts, as
well as the metadata on the rows (genes) and columns (cells).
bm_rat <- bodymapRat()
# Get the expression data
counts = assay(bm_rat)
dim(counts)## [1] 32637 652counts[1:5, 1:5]## SRR1169893 SRR1169894 SRR1169895 SRR1169896 SRR1169897
## ENSRNOG00000000001 1 0 0 1 4
## ENSRNOG00000000007 1 1 0 3 0
## ENSRNOG00000000008 7 4 2 3 7
## ENSRNOG00000000009 0 0 0 0 1
## ENSRNOG00000000010 0 1 0 0 0# Get the meta data along columns
head(colData(bm_rat))## DataFrame with 6 rows and 22 columns
## sraExperiment sraRun title geoAccession sraSample
## <character> <character> <character> <factor> <factor>
## SRR1169893 SRX471368 SRR1169893 Adr_F_002_1 GSM1328469 SRS558114
## SRR1169894 SRX471368 SRR1169894 Adr_F_002_1 GSM1328469 SRS558114
## SRR1169895 SRX471369 SRR1169895 Adr_F_002_2 GSM1328470 SRS558115
## SRR1169896 SRX471369 SRR1169896 Adr_F_002_2 GSM1328470 SRS558115
## SRR1169897 SRX471370 SRR1169897 Adr_F_002_3 GSM1328471 SRS558116
## SRR1169898 SRX471370 SRR1169898 Adr_F_002_3 GSM1328471 SRS558116
## BioSample avgLength organ sex stage techRep
## <factor> <integer> <character> <character> <numeric> <integer>
## SRR1169893 SAMN02642886 50 Adrenal F 2 1
## SRR1169894 SAMN02642886 50 Adrenal F 2 2
## SRR1169895 SAMN02642867 50 Adrenal F 2 1
## SRR1169896 SAMN02642867 50 Adrenal F 2 2
## SRR1169897 SAMN02642894 50 Adrenal F 2 1
## SRR1169898 SAMN02642894 50 Adrenal F 2 2
## colOrgan mix rnaRIN barcode instrument
## <character> <character> <character> <character> <character>
## SRR1169893 brown M1 9.3 11 HWI-ST845
## SRR1169894 brown M1 9.3 11 HWI-ST845
## SRR1169895 brown M1 9.1 5 HWI-ST845
## SRR1169896 brown M1 9.1 5 HWI-ST845
## SRR1169897 brown M1 9.5 3 HWI-ST1131
## SRR1169898 brown M1 9.5 3 HWI-ST1195
## runID fcID fcLane tile xtile
## <character> <character> <character> <character> <character>
## SRR1169893 120326 D0VTJACXX 2 1101 1506
## SRR1169894 120525 D10G7ACXX 2 1101 1394
## SRR1169895 120326 D0VTJACXX 5 1101 1170
## SRR1169896 120525 D10G7ACXX 5 1101 1650
## SRR1169897 120424 C0P4UACXX 4 1101 1675
## SRR1169898 120525 C0TDUACXX 4 1101 1138
## ytile
## <character>
## SRR1169893 2000
## SRR1169894 2133
## SRR1169895 2029
## SRR1169896 2126
## SRR1169897 2216
## SRR1169898 2067The data in this package are used as an example
data set in the
qsmooth Bioconductor package.
sessionInfo()## R version 4.5.0 RC (2025-04-04 r88126)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0 LAPACK version 3.12.0
##
## 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] bodymapRat_1.24.0 ExperimentHub_2.16.0
## [3] AnnotationHub_3.16.0 BiocFileCache_2.16.0
## [5] dbplyr_2.5.0 SummarizedExperiment_1.38.0
## [7] Biobase_2.68.0 GenomicRanges_1.60.0
## [9] GenomeInfoDb_1.44.0 IRanges_2.42.0
## [11] S4Vectors_0.46.0 BiocGenerics_0.54.0
## [13] generics_0.1.3 MatrixGenerics_1.20.0
## [15] matrixStats_1.5.0 knitr_1.50
## [17] BiocStyle_2.36.0
##
## loaded via a namespace (and not attached):
## [1] KEGGREST_1.48.0 xfun_0.52 bslib_0.9.0
## [4] lattice_0.22-7 vctrs_0.6.5 tools_4.5.0
## [7] curl_6.2.2 tibble_3.2.1 AnnotationDbi_1.70.0
## [10] RSQLite_2.3.9 blob_1.2.4 pkgconfig_2.0.3
## [13] Matrix_1.7-3 lifecycle_1.0.4 GenomeInfoDbData_1.2.14
## [16] compiler_4.5.0 Biostrings_2.76.0 htmltools_0.5.8.1
## [19] sass_0.4.10 yaml_2.3.10 pillar_1.10.2
## [22] crayon_1.5.3 jquerylib_0.1.4 DelayedArray_0.34.0
## [25] cachem_1.1.0 abind_1.4-8 mime_0.13
## [28] tidyselect_1.2.1 digest_0.6.37 purrr_1.0.4
## [31] dplyr_1.1.4 bookdown_0.43 BiocVersion_3.21.1
## [34] fastmap_1.2.0 grid_4.5.0 cli_3.6.4
## [37] SparseArray_1.8.0 magrittr_2.0.3 S4Arrays_1.8.0
## [40] withr_3.0.2 filelock_1.0.3 UCSC.utils_1.4.0
## [43] rappdirs_0.3.3 bit64_4.6.0-1 rmarkdown_2.29
## [46] XVector_0.48.0 httr_1.4.7 bit_4.6.0
## [49] png_0.1-8 memoise_2.0.1 evaluate_1.0.3
## [52] rlang_1.1.6 glue_1.8.0 DBI_1.2.3
## [55] BiocManager_1.30.25 jsonlite_2.0.0 R6_2.6.1