RNA-seq training differential analysis — transcript_training

Use DESeq2 to perform a likelihood ratio test to test the effect of training across time points. Analysis is performed separately for males and females.

Usage

transcript_training_da(
  tissue,
  covariates = c("pct_globin", "RIN", "pct_umi_dup", "median_5_3_bias"),
  outliers = na.omit(MotrpacRatTraining6moData::OUTLIERS$viallabel),
  rdata_outfile = NULL,
  overwrite = FALSE,
  verbose = FALSE
)

Arguments

tissue: character, tissue abbreviation, one of MotrpacRatTraining6moData::TISSUE_ABBREV
covariates: character vector of covariates that correspond to column names of MotrpacRatTraining6moData::TRNSCRPT_META. Defaults to covariates that were used for the manuscript.
outliers: vector of viallabels to exclude during differential analysis. Defaults to [MotrpacRatTraining6moData::OUTLIERS]$viallabel
rdata_outfile: NULL or path in which to save DESeq2 objects in an RData file
overwrite: boolean, whether to overwrite the file if rdata_outfile exists
verbose: boolean, whether to print messages

Value

a data frame with one row per gene:

feature_ID: character, MoTrPAC feature identifier
assay: character, assay abbreviation, one of MotrpacRatTraining6moData::ASSAY_ABBREV
assay_code: character, assay code used in data release. See MotrpacBicQC::assay_codes.
tissue: character, tissue abbreviation, one of MotrpacRatTraining6moData::TISSUE_ABBREV
tissue_code: character, tissue code used in data release. See MotrpacBicQC::bic_animal_tissue_code.
removed_samples_male: character, comma-separated list of male outliers (vial labels) removed from differential analysis
removed_samples_female: character, comma-separated list of female outliers (vial labels) removed from differential analysis
lrt_male: double, likelihood ratio test statistic for males
lrt_female: double, likelihood ratio test statistic for females
p_value_male: double, nominal LRT p-value for males
p_value_female: double, nominal LRT p-value for females
full_model_male: character, full model used in LRT for males
full_model_female: character, full model used in LRT for females
reduced_model_male: character, reduced model used in LRT for males
reduced_model_female: character, reduced model used in LRT for females
p_value: double, combined male and female nominal p-value using the sum of logs

Examples

if (FALSE) { # \dontrun{
# Perform differential analysis for expressed genes in brown adipose tissue 
# with default parameters, i.e., outliers and covariates used for the manuscript
da = transcript_training_da("BAT")

# Same as above but save the [DESeq2::DESeq2()] DESeqResults objects in an RData file 
da = transcript_training_da("BAT", 
                            rdata_outfile = "~/test/BAT_RNA_training-da.RData", 
                            overwrite = TRUE)
} # }