This function does the necessary computation to detect batch effects in your data. See details for more.
detectBatchEffects(object, verbose = TRUE)| object | A valid cypro object. |
|---|---|
| verbose | Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.) |
An updated version of the input cypro-object.
Batch effects result from undesired technical variation and can lead to
misinterpretation and false conclusion. This does two things:
First it creates summarized median profiles for each well by grouping the
cell data by well plate name and well via dplyr::group_by() and
then summarizes all stat variables via dplyr::summarize_all().
It then computes the distances between all wells. If wells of well plates that were set up in one batch cluster together it is likely that batch effects impact your data.
Hint: This logic only applies to experiment designs in which conditions are randomly distributed over well plates as a wells condition highly impacts its median profile.
plotBatchHeatmap(), getBatchEffectDf()