create_input_rnaseq: Creates an RNA-seq input object for downstream analysis
In ddeweerd/MODifieRDev: MODifieRDev

Description Usage Arguments Details Value See Also

The MODifieR input objects can be used in downstream analysis for the disease module inference methods included in this package.

create_input_rnaseq(count_matrix, group1_indici, group2_indici,
  group1_label, group2_label, expression = T,
  differential_expression = T, use_adjusted = T,
  normalize_quantiles = F)

`count_matrix`	Matrix containing raw RNA-seq counts
`group1_indici`	vector containing indici for samples belonging to group 1 (Column numbers)
`group2_indici`	vector containing indici for samples belonging to group 2 (Column numbers)
`group1_label`	Label for each group 1, for example "patient" or "control"
`group2_label`	Label for each group 2, for example "patient" or "control"
`expression`	boolean, calculate expression values?
`differential_expression`	boolean, calculate differentially expressed data?
`use_adjusted`	boolean, use adjusted p value for differential expression analysis?
`normalize_quantiles`	boolean, Normalize quantiles for WGCNA-based methods?

The function creates an input object to be used in all disease module inference methods. Differentially expressed genes are calculated using generalized linear models from the edgeR package. For WGCNA-based methods raw counts are normalized using the varianceStabilizingTransformation from the DESeq2 package. Optionally, Quantile normalization using the normalize.quantiles function from the preprocessCore can be applied.

The function returns an object of class "MODifieR_input". The object is a named list containing the following components:

`diff_genes`	A 2 two column data.frame where the first column are genes and the second column unadjusted p-values obtained by differential expression analysis
`edgeR_deg_table`	A data.frame from `edgeR glmQLFit`
`annotated_exprs_matrix`	A matrix where the rows are genes and the columns samples. Raw counts have been normalized with `varianceStabilizingTransformation` and optionally quantile normalized
`count_matrix`	A matrix, the original input count matrix
`group_indici`	A named list containing 2 numeric vectors. The names are the group labels and the values are the group indici