Description Usage Arguments Details Value Examples
This function extracts abundance matrix and meta-data in the chosen orientation from the input.
1 2 3 4 5 6 7 | mbecGetData(
input.obj,
orientation = "fxs",
required.col = NULL,
type = c("otu", "ass", "cor", "clr", "tss"),
label = character()
)
|
input.obj |
MbecData object |
orientation, |
Select either 'fxs' or 'sxf' to retrieve features in rows or columns respectively. |
required.col |
Vector of column names that are required from the covariate-table. |
type |
Specify which type of data to add, by using one of 'ass' (Assessement), 'cor' (Correction), 'clr' (Cumulative Log-Ratio) or 'tss' (Total Scaled-Sum). |
label |
For types 'ass' and 'cor' this specifies the name within the lists. |
The parameter 'orientation' determines if the output has features as columns (sxf) or if the columns contain samples (fxs). This is mainly used to retrieve correctly oriented matrices for the different analysis and correction functions.
The parameter 'required.col' is a vector of column names (technically positions would work) in the metadata, that are required for the analysis at hand. The function actually only checks if they are present in the data, but it will return the whole meta-frame.
The argument type determines which slot to access, i.e. the base matrices for un-transformed counts "otu", total sum-scaled counts "tss", cumulative log-ratio transformed counts "clr" and batch effect corrected counts "cor" and assessment vectors "ass". The later two additionally require the use of the argument 'label' that specifies the name within the respective lists of corrections and assessments.
A list that contains count-matrix (in chosen orientation) and meta-data table.
1 2 3 4 5 6 7 8 9 10 11 | # This will return the un-transformed (OTU) abundance matrix with features as
# columns and it will test if the columns "group" and "batch" are present in
# the meta-data table.
list.obj <- mbecGetData(input.obj=dummy.mbec, orientation="sxf",
required.col=c("group","batch"), type="otu")
# This will return the clr-transformed abundance matrix with features as
# rows and it will test if the columns "group" and "batch" are present in
# the meta-data table.
list.obj <- mbecGetData(input.obj=dummy.mbec, orientation="fxs",
required.col=c("group","batch"), type="clr")
|
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