get_differential_transcript_abundance_bulk {tidybulk} | R Documentation |
Get differential transcription information to a tibble using edgeR.
get_differential_transcript_abundance_bulk( .data, .formula, .sample = NULL, .transcript = NULL, .abundance = NULL, .contrasts = NULL, method = "edgeR_quasi_likelihood", test_above_log2_fold_change = NULL, scaling_method = "TMM", omit_contrast_in_colnames = FALSE, prefix = "", .sample_total_read_count = NULL )
.data |
A tibble |
.formula |
a formula with no response variable, referring only to numeric variables |
.sample |
The name of the sample column |
.transcript |
The name of the transcript/gene column |
.abundance |
The name of the transcript/gene abundance column |
.contrasts |
A character vector. See edgeR makeContrasts specification for the parameter 'contrasts'. If contrasts are not present the first covariate is the one the model is tested against (e.g., ~ factor_of_interest) |
method |
A string character. Either "edgeR_quasi_likelihood" (i.e., QLF), "edgeR_likelihood_ratio" (i.e., LRT) |
test_above_log2_fold_change |
A positive real value. This works for edgeR and limma_voom methods. It uses the 'treat' function, which tests that the difference in abundance is bigger than this threshold rather than zero https://pubmed.ncbi.nlm.nih.gov/19176553. |
scaling_method |
A character string. The scaling method passed to the backend function (i.e., edgeR::calcNormFactors; "TMM","TMMwsp","RLE","upperquartile") |
omit_contrast_in_colnames |
If just one contrast is specified you can choose to omit the contrast label in the colnames. |
.sample_total_read_count |
A tibble with edgeR results