tcgaNormalizer: Normalize RNA-seq or miRNA-seq dataset
In YC3/mirNet: microRNA netowrk analyses

Description Usage Arguments Value See Also Examples

tcgaNormalizer normalizes RNA-seq expression dataset by 1) removing genes with > 70% NA values across samples or across genes/microRNAs, 2) removing genes with low variation (sd < 0.2) across samples, 3) log2 transformation and 4) quantile normalization. For miRNA-seq data removing microNRAs with > 95% NA values across samples in step 2).

tcgaNormalizer(
  data,
  dataType,
  mir_na_thre = 0.95,
  mir_sd_thre = 0.2,
  plotFig = TRUE,
  filename = NULL
)

`data`	A data matrix, with rows referring to genes/microRNAs and columns to samples, can be the output from `tcgaTableGenerator` or `tcgaConvRownames`.
`dataType`	A string, 'microRNA' for microRNA-seq data or 'mRNA' for RNA-seq data.
`mir_na_thre`	The threshold used to remove microRNAs with too many NAs across samples, defualt to 95%.
`mir_sd_thre`	The threshold used to remove microRNAs with low variation across samples, defualt to 0.2.
`plotFig`	Logic, 'TRUE' if you want to plot a scatter plot of NA proportions, 'FALSE' otherwise.
`filename`	The name of output scatterplot of NA proportions across samples and genes/microRNAs.

A data matrix with normalized gene/microRNA expression data. A scatter plots of NA proportions across samples and genes/microRNAs.

tcgaTableGenerator for generating a gene expression data matrix from single FPKM files downloaded from GDC Data Portal, tcgaConvRownames for converting rownames of a data matrix.

1 2	tcgaNormalizer(gen.luad.m, dataType = 'mRNA', filename = 'scatter plot of genes') tcgaNormalizer(mir.luad.m, dataType = 'microRNA', filename = 'scatter plot of miNRAs')