bametric {bapred}

Diverse metrics for quality of (adjusted) batch data

Description

Diverse metrics measuring the severeness of batch effects in (batch effect adjusted) data or the performance of certain analyses performed using the latter. This is a wrapper function for the following functions, where each of them calculates a certain metric: sepscore, avedist, kldist, skewdiv, pvcam, diffexprm and corba. For details see the documentation of the latter.

Usage

bametric(xba, batch, y, x, metric = c("sep", "avedist", "kldist", 
  "skew", "pvca", "diffexpr", "cor"), method, ...)

Arguments

xba

matrix. The covariate matrix, raw or after batch effect adjustment. observations in rows, variables in columns.

batch

factor. Batch variable. Each factor level (or 'category') corresponds to one of the batches. For example, if there are four batches, this variable would have four factor levels and observations with the same factor level would belong to the same batch.

y

factor. Binary target variable. Has to have two factor levels, where each of them correponds to one of the two classes of the target variable. Only used for metric = "pvca" and metric = "diffexpr".

x

matrix. The covariate matrix before batch effect adjustment. observations in rows, variables in columns.

metric

character. The metric to use.

method

character. The batch effect adjustment method to use for metric = "diffexpr".

...

additional arguments to be passed to sepscore or pvcam.

Value

Value of the respective metric

Author(s)

Roman Hornung

References

Boltz, S., Debreuve, E., Barlaud, M. (2009). High-dimensional statistical measure for region-of-interest tracking. Transactions in Image Processing 18(6):1266-1283, <doi: 10.1109/TIP.2009.2015158>.

Geyer, C. J., Meeden, G., D. (2005). Fuzzy and randomized confidence intervals and p-values (with discussion). Statistical Science 20(4):358-387, <doi: 10.1214/088342305000000340>.

Hornung, R., Boulesteix, A.-L., Causeur, D. (2016). Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment. BMC Bioinformatics 17:27, <doi: 10.1186/s12859-015-0870-z>.

Lazar, C., Meganck, S., Taminau, J., Steenhoff, D., Coletta, A., Molter,C., Weiss-Solís, D. Y., Duque, R., Bersini, H., Nowé, A. (2012). Batch effect removal methods for microarray gene expression data integration: a survey. Briefings in Bioinformatics 14(4):469-490, <doi: 10.1093/bib/bbs037>.

Lee, J. A., Dobbin, K. K., Ahn, J. (2014). Covariance adjustment for batch effect in gene expression data. Statistics in Medicine 33:2681-2695, <doi: 10.1002/sim.6157>.

Li, J., Bushel, P., Chu, T.-M., Wolfinger, R.D. (2009). Principal variance components analysis: Estimating batch effects in microarray gene expression data. In: Scherer, A. (ed) Batch Effects and Noise in Microarray Experiments: Sources and Solutions, John Wiley & Sons, Chichester, UK, <doi: 10.1002/9780470685983.ch12>.

Shabalin, A. A., Tjelmeland, H., Fan, C., Perou, C. M., Nobel, A. B. (2008). Merging two gene-expression studies via cross-platform normalization. Bioinformatics 24(9):1154-1160, <doi: 10.1093/bioinformatics/btn083>.

Examples

data(autism)

# Random subset of 150 variables:
set.seed(1234)
Xsub <- X[,sample(1:ncol(X), size=150)]

# In cases of batches with more than 20 observations
# select 20 observations at random:
subinds <- unlist(sapply(1:length(levels(batch)), function(x) {
  indbatch <- which(batch==x)
  if(length(indbatch) > 20)
    indbatch <- sort(sample(indbatch, size=20))
  indbatch
}))
Xsub <- Xsub[subinds,]
batchsub <- batch[subinds]
ysub <- y[subinds]




Xsubadj <- ba(x=Xsub, y=ysub, batch=batchsub, method = "combat")$xadj


bametric(xba=Xsub, batch=batchsub, metric = "sep")
bametric(xba=Xsubadj, batch=batchsub, metric = "sep")

bametric(xba=Xsub, batch=batchsub, metric = "avedist")
bametric(xba=Xsubadj, batch=batchsub, metric = "avedist")

bametric(xba=Xsub, batch=batchsub, metric = "kldist")
bametric(xba=Xsubadj, batch=batchsub, metric = "kldist")

bametric(xba=Xsub, batch=batchsub, metric = "skew")
bametric(xba=Xsubadj, batch=batchsub, metric = "skew")

bametric(xba=Xsub, batch=batchsub, y=ysub, metric = "pvca")
bametric(xba=Xsubadj, batch=batchsub, y=ysub, metric = "pvca")

bametric(x=Xsub, batch=batchsub, y=ysub, metric = "diffexpr", 
  method = "combat")

bametric(xba=Xsubadj, x=Xsub, metric = "cor")