The TransOmicsData package contains datasets spanning various biological contexts such as in vitro embryonic and tissue-specific development in mouse and human. It covers multiple omics sequencing technologies such as RNAseq, mass spectrometry and ChIP-seq. This package was developed to provide convenient access to raw or pre-processed data for comparative trans-omics analysis.
The data stored in this package can be retrieved using ExperimentHub.
# if (!requireNamespace("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("ExperimentHub")library(ExperimentHub)
refreshHub(hubClass = "ExperimentHub")## ExperimentHub with 8286 records
## # snapshotDate(): 2024-04-29
## # $dataprovider: Eli and Edythe L. Broad Institute of Harvard and MIT, NCBI,...
## # $species: Homo sapiens, Mus musculus, Saccharomyces cerevisiae, Drosophila...
## # $rdataclass: SummarizedExperiment, data.frame, ExpressionSet, matrix, char...
## # additional mcols(): taxonomyid, genome, description,
## # coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
## # rdatapath, sourceurl, sourcetype
## # retrieve records with, e.g., 'object[["EH1"]]'
##
## title
## EH1 | RNA-Sequencing and clinical data for 7706 tumor samples from The...
## EH166 | ERR188297
## EH167 | ERR188088
## EH168 | ERR188204
## EH169 | ERR188317
## ... ...
## EH9535 | Seurat Vizgen test data
## EH9536 | High multiplicity-of-infection CRISPRi screen of putative enhanc...
## EH9537 | High multiplicity-of-infection CRISPRi screen of putative enhanc...
## EH9538 | Low multiplicity-of-infection CRISPRko screen of gene transcript...
## EH9539 | Parse Biosciences single-cell CRISPR screenehub <- ExperimentHub()
myfiles <- query(ehub, "TransOmicsData")
myfiles## ExperimentHub with 12 records
## # snapshotDate(): 2024-04-29
## # $dataprovider: PRIDE, NCBI
## # $species: Mus musculus, Homo sapiens
## # $rdataclass: SummarizedExperiment
## # additional mcols(): taxonomyid, genome, description,
## # coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
## # rdatapath, sourceurl, sourcetype
## # retrieve records with, e.g., 'object[["EH8536"]]'
##
## title
## EH8536 | Chen organoid phosphoproteome
## EH8537 | Chen organoid proteome
## EH8538 | Chen organoid transcriptome
## EH8539 | Xiao myogenesis differentation phosphoproteome
## EH8540 | Xiao myogenesis differentiation proteome
## ... ...
## EH8543 | Yang ESC epigenome
## EH8544 | Yang ESC phosphoproteome
## EH8545 | Yang ESC proteome
## EH8546 | Yang ESC transcriptome
## EH9515 | Chen organoid sctranscriptome# BiocManager::install("TransOmicsData")To list the summarized metadata for all datasets in the package:
library(TransOmicsData)
listDatasets()## DataFrame with 3 rows and 6 columns
## Title Description Omics Species
## <character> <character> <character> <character>
## 1 chen-organoid neural organoid diff.. phosphoproteome, pro.. human
## 2 xiao-myogenesis C2C12 myogenesis dif.. phosphoproteome, pro.. mouse
## 3 yang-esc ESC to epiLC differe.. epigenome, phosphopr.. mouse
## RDataPath Reference
## <character> <character>
## 1 TransOmicsData/0.99... Chen et al. Trans-om..
## 2 TransOmicsData/0.99... Xiao et al. Time-res..
## 3 TransOmicsData/0.99... Yang et al. Multi-om..TransOmicsDataWe hope that TransOmicsData will be useful for your research. Please use the following information to cite the package. Thank you!
## Citation info
citation("TransOmicsData")## To cite TransOmicsData in publications use:
##
## Chen C, Xiao D, Yang P (2024). _TransOmicsData: a collection of
## trans-omics data covering a wide range of biological systems._.
## University of Sydney, Sydney, Australia.
## doi:10.18129/B9.bioc.TransOmicsData
## <https://doi.org/10.18129/B9.bioc.TransOmicsData>,
## <https://github.com/PYangLab/TransOmicsData>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {TransOmicsData: a collection of trans-omics data covering a wide range of biological systems.},
## author = {Carissa Chen and Di Xiao and Pengyi Yang},
## organization = {University of Sydney},
## address = {Sydney, Australia},
## year = {2024},
## url = {https://github.com/PYangLab/TransOmicsData},
## doi = {10.18129/B9.bioc.TransOmicsData},
## }## R version 4.4.0 (2024-04-24)
## 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 LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] TransOmicsData_1.0.1 ExperimentHub_2.12.0 AnnotationHub_3.12.0 BiocFileCache_2.12.0 dbplyr_2.5.0
## [6] BiocGenerics_0.50.0 BiocStyle_2.32.0
##
## loaded via a namespace (and not attached):
## [1] KEGGREST_1.44.0 xfun_0.43 bslib_0.7.0 Biobase_2.64.0
## [5] vctrs_0.6.5 tools_4.4.0 generics_0.1.3 stats4_4.4.0
## [9] curl_5.2.1 tibble_3.2.1 fansi_1.0.6 AnnotationDbi_1.66.0
## [13] RSQLite_2.3.6 blob_1.2.4 pkgconfig_2.0.3 S4Vectors_0.42.0
## [17] lifecycle_1.0.4 GenomeInfoDbData_1.2.12 compiler_4.4.0 Biostrings_2.72.0
## [21] GenomeInfoDb_1.40.0 htmltools_0.5.8.1 sass_0.4.9 yaml_2.3.8
## [25] pillar_1.9.0 crayon_1.5.2 jquerylib_0.1.4 cachem_1.0.8
## [29] mime_0.12 tidyselect_1.2.1 digest_0.6.35 dplyr_1.1.4
## [33] purrr_1.0.2 bookdown_0.39 BiocVersion_3.19.1 fastmap_1.1.1
## [37] cli_3.6.2 magrittr_2.0.3 utf8_1.2.4 withr_3.0.0
## [41] filelock_1.0.3 UCSC.utils_1.0.0 rappdirs_0.3.3 bit64_4.0.5
## [45] rmarkdown_2.26 XVector_0.44.0 httr_1.4.7 bit_4.0.5
## [49] png_0.1-8 memoise_2.0.1 evaluate_0.23 knitr_1.46
## [53] IRanges_2.38.0 rlang_1.1.3 glue_1.7.0 DBI_1.2.2
## [57] BiocManager_1.30.23 jsonlite_1.8.8 R6_2.5.1 zlibbioc_1.50.0