Correct batch effect with ComBat-seq method — adjust

Batch effect of RiboMethSeq data can be adjusted using the ComBat-seq method. adjust_bias is a wrapper to perform ComBat-seq adjustment.

It will return a new RiboClass with adjusted read end count values and C-scores automatically recomputed with the same setup parameters.

Usage

adjust_bias(ribo, batch, ncores = 1, ...)

Arguments

ribo: a RiboClass object.
batch: Name of the column in metadata that contains the batch number.
ncores: Number of cores to use in case of multithreading.
...: Parameters to pass to sva's ComBat_seq function.

Value

RiboClass with adjusted read end count values and automatically recomputed C-scores.

Details

You must have a column with the batch number for each sample in your RiboClass’s metadata.

References

Yuqing Zhang, Giovanni Parmigiani, W Evan Johnson, ComBat-seq: batch effect adjustment for RNA-seq count data, NAR Genomics and Bioinformatics, Volume 2, Issue 3, 1 September 2020, lqaa078, https://doi.org/10.1093/nargab/lqaa078

Examples

data('ribo_toy')
ribo_toy_two <- keep_ribo_samples(ribo_toy,c('S1','RNA1','S7','RNA2'))
ribo_toy_adjusted <- adjust_bias(ribo_toy_two,'run') 
#> Found 2 batches
#> Using null model in ComBat-seq.
#> Adjusting for 0 covariate(s) or covariate level(s)
#> Estimating dispersions
#> Fitting the GLM model
#> Shrinkage off - using GLM estimates for parameters
#> Adjusting the data
#> Recomputing c-score with the following parameters :
#> - C-score method : median
#> - Flanking window : 6