Description Usage Arguments Details Value Examples
View source: R/mbecs_analyses.R
Takes two covariates, i.e., group and batch, and computes the RLE-plot over the grouping of the first covariate, colored by the second covariate. Effectively illustrating the relative expression between samples from different batches within the respective study groups. Other covariates can be chosen as input and the function will check for factors and convert if necessary. Categorical factors, e.g., group membership, sex and batch, produce the best result.
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input.obj |
MbecData-object |
model.vars |
two covariates of interest to select by. First relates to 'batch' and the second to relevant grouping. |
type |
Which abundance matrix to use for the calculation. |
label |
Which corrected abundance matrix to use for analysis. |
return.data |
logical if TRUE returns the data.frame required for plotting. Default (FALSE) will return plot object. |
The function returns either a plot-frame or the finished ggplot object. Input is an MbecData-object. If cumulative log-ratio (clr) and total sum-scaled (tss) abundance matrices are part of the input, i.e., 'mbecTransform()' was used, they can be selected as input by using the 'type' argument with either "otu", "clr" or "tss". If batch effect corrected matrices are available, they can be used by specifying the 'type' argument as "cor" and using the 'label' argument to select the appropriate matrix by its denominator, e.g., for batch correction method ComBat this would be "bat", for RemoveBatchEffects from the limma package this is "rbe". Default correction method-labels are "ruv3", "bmc","bat","rbe","pn","svd".
The combination of 'type' and 'label' argument basically accesses the attribute 'cor', a list that stores all matrices of corrected counts. This list can also be accessed via getter and setter methods. Hence, the user can supply their own matrices with own names.
Either a ggplot2 object or a formatted data-frame to plot from.
1 2 3 4 5 6 7 | # This will return the data.frame for plotting.
data.RLE <- mbecRLE(input.obj=dummy.mbec, type="clr",
model.vars=c('group','batch'), return.data=TRUE)
# This will return the ggplot2 object for display, saving and modification.
plot.RLE <- mbecRLE(input.obj=dummy.mbec, model.vars=c('group','batch'),
type="clr", return.data=FALSE)
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