Description Usage Arguments Details Value See Also
Estimate experimental batch effects.
1 2 3 4 5 6 7 8 9 10 11 | getBatchEffects(x, ...)
## Default S3 method:
getBatchEffects(x, ...)
## S3 method for class 'concensusWorkflow'
getBatchEffects(x, ...)
## S3 method for class 'concensusDataSet'
getBatchEffects(x, grouping = c("compound",
"concentration", "strain"), ...)
|
x |
concensusWorkflow or concensusDataSet. |
... |
Other arguments. |
Columns in the data
attribute of the concensusDataSet
object which
have fewer than 100 unique values and which are not named according to a list of stopwords are assumed to be experimental
handling annotations, and will be modeled using a Negative Binomial GLM, using dispersion parameters in the dispersion
attribute.
Only the negative control observations will be used for estimating batch effects.
A new column, predicted_null_count
, is added to data
of concensusDataSet
with a prediction of
number of counts for every observation, assuming only batch effects (and no real effect of interest).
If the model fitting fails, rather than throw off the whole pipeline, a predicted_null_count
value of 1
is used.
concensusWorkflow or concensusDataSet with a new batch_effect_model
and a new predicted_null_count
column
in the data
attribute.
glm
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