Combine normalized sample-level data from the specified tissues and omes(s)/assay(s). If no tissues or omes are specified, all data is returned. In order to combine data from different tissues and data types, sample-specific vial labels are converted to animal-specific Participant IDs (PIDs).
Usage
combine_normalized_data(
tissues = MotrpacRatTraining6moData::TISSUE_ABBREV,
assays = MotrpacRatTraining6moData::ASSAY_ABBREV,
include_epigen = FALSE,
scratchdir = ".",
training_regulated_only = FALSE,
exclude_outliers = FALSE,
nrows = Inf
)
Arguments
- tissues
optional character vector of tissue abbreviations, one of MotrpacRatTraining6moData::TISSUE_ABBREV.
- assays
optional character vector of assay abbreviations, one of MotrpacRatTraining6moData::ASSAY_ABBREV
- include_epigen
bool, whether to include the full ATAC or METHYL differential analysis results from Google Cloud Storage. Only relevant if
assays
includes "ATAC" or "METHYL".FALSE
by default.- scratchdir
character, local directory in which to download data from the web. Current working directory by default. Only relevant if
assays
includes "ATAC" or "METHYL".- training_regulated_only
bool, whether to filter features down to those training-regulated at 5% FDR
- exclude_outliers
bool, whether to remove sample outliers specified by MotrpacRatTraining6moData::OUTLIERS
- nrows
integer, number of rows to return from each dataset. Defaults to Inf. Useful to return a subset of a large data frame for tests.
Examples
if (FALSE) { # \dontrun{
# Return all normalized RNA-seq data
data = combine_normalized_data(assays = "TRNSCRPT")
} # }
# Return all normalized proteomics data. Exclude outliers
data = combine_normalized_data(assays = c("PROT","UBIQ","PHOSPHO","ACETYL"),
exclude_outliers = TRUE)
#> PROT_CORTEX_NORM_DATA
#> PROT_HEART_NORM_DATA
#> PROT_KIDNEY_NORM_DATA
#> PROT_LIVER_NORM_DATA
#> PROT_LUNG_NORM_DATA
#> PROT_SKMGN_NORM_DATA
#> PROT_WATSC_NORM_DATA
#> UBIQ_HEART_NORM_DATA
#> UBIQ_LIVER_NORM_DATA
#> PHOSPHO_CORTEX_NORM_DATA
#> PHOSPHO_HEART_NORM_DATA
#> PHOSPHO_KIDNEY_NORM_DATA
#> PHOSPHO_LIVER_NORM_DATA
#> PHOSPHO_LUNG_NORM_DATA
#> PHOSPHO_SKMGN_NORM_DATA
#> PHOSPHO_WATSC_NORM_DATA
#> ACETYL_HEART_NORM_DATA
#> ACETYL_LIVER_NORM_DATA
if (FALSE) { # \dontrun{
# Return normalized ATAC-seq data for training-regulated features
data = combine_normalized_data(assays = "ATAC", training_regulated_only = TRUE)
# Return normalized ATAC-seq data for the first 1000 features in each tissue
data = combine_normalized_data(assays = "ATAC",
nrows = 1000,
scratchdir = "/tmp",
include_epigen = TRUE)
} # }
# Return all normalized metabolomics data
data = combine_normalized_data(assays = "METAB")
#> METAB ADRNL normalized data from METAB_NORM_DATA_FLAT
#> METAB BAT normalized data from METAB_NORM_DATA_FLAT
#> METAB BLOOD normalized data from METAB_NORM_DATA_FLAT
#> METAB COLON normalized data from METAB_NORM_DATA_FLAT
#> METAB CORTEX normalized data from METAB_NORM_DATA_FLAT
#> METAB HEART normalized data from METAB_NORM_DATA_FLAT
#> METAB HIPPOC normalized data from METAB_NORM_DATA_FLAT
#> METAB HYPOTH normalized data from METAB_NORM_DATA_FLAT
#> METAB KIDNEY normalized data from METAB_NORM_DATA_FLAT
#> METAB LIVER normalized data from METAB_NORM_DATA_FLAT
#> METAB LUNG normalized data from METAB_NORM_DATA_FLAT
#> METAB OVARY normalized data from METAB_NORM_DATA_FLAT
#> METAB PLASMA normalized data from METAB_NORM_DATA_FLAT
#> METAB SKM-GN normalized data from METAB_NORM_DATA_FLAT
#> METAB SKM-VL normalized data from METAB_NORM_DATA_FLAT
#> METAB SMLINT normalized data from METAB_NORM_DATA_FLAT
#> METAB SPLEEN normalized data from METAB_NORM_DATA_FLAT
#> METAB TESTES normalized data from METAB_NORM_DATA_FLAT
#> METAB VENACV normalized data from METAB_NORM_DATA_FLAT
#> METAB WAT-SC normalized data from METAB_NORM_DATA_FLAT