Install the package:
library(devtools)
install_github("pwirapati/nsx")
Load the package
library(nsx)
Prepare the input data by unzipping the RCC files into a directory. The files can also be individually compressed (such as *.RCC.gz typically provided in NCBI GEO).
As an example, we use a publicly available dataset from NCBI GEO.
download.file("https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE143382&format=file","GSE143382_RAW.tar")
untar("GSE143382_RAW.tar",exdir="RCC") # extract the RCC files into directory RCC
list.files("RCC")
Read in the raw data:
raw_data <- readRCCset("RCC")
Plot data distribution:
rawQCplot(raw_data)
(Subsets can be shown by supplying a set of indices. For example, adding o=1:12 will show only
the first 12. Adding o=12:1 will show the same set in reversed order.)
Normalize the data:
norm_data <- bgsc_norm(raw_data)
The normalized data matrix can be found in norm_data$z.
Show normalization curve of an individual sample:
bgsc_plot( norm_data, 1)
(The number refers to the sample position in the normalized data matrix norm_data$z).