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", significance_threshold = 0.05, minimum_counts = 10, minimum_proportion = 0.7, fill_missing_values = FALSE, scaling_method = "TMM", omit_contrast_in_colnames = FALSE )
.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) |
significance_threshold |
A real between 0 and 1 |
minimum_counts |
A positive integer. Minimum counts required for at least some samples. |
minimum_proportion |
A real positive number between 0 and 1. It is the threshold of proportion of samples for each transcripts/genes that have to be characterised by a cmp bigger than the threshold to be included for scaling procedure. |
fill_missing_values |
A boolean. Whether to fill missing sample/transcript values with the median of the transcript. This is rarely needed. |
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. |
A tibble with edgeR results