GSE68172 Processing Pipeline

Publication

Nature cancer (2020) — PMID 34109316

Dataset

LAA expression profiles on LSC compared to other tissues

1. 1

   The data were analyzed with BRB ArrayTools using RMA.

   BRB ArrayTools vNot specified (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # BRB ArrayTools is primarily a GUI-based software for microarray data analysis.
   # Direct command-line execution for specific analysis steps like RMA (Robust Multi-array Average)
   # is not typically performed via a single bash command like other CLI tools.
   # Users interact with the software through its graphical interface to load raw microarray data (e.g., .CEL files),
   # select analysis methods (e.g., RMA for normalization), and view results.
   
   # Installation (conceptual - typically involves downloading and installing a GUI application):
   # For Windows/macOS, download the installer from the official BRB ArrayTools website.
   # Example of a conceptual command if it were a CLI tool (this is NOT how BRB ArrayTools is used):
   # brb_arraytools --method RMA --input raw_microarray_data.CEL --output normalized_data.txt
   # The analysis is performed interactively within the GUI, where RMA is selected as a normalization method.

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2. 2

   Intensity values were log2 transformed

   R (Inferred with models/gemini-2.5-flash) vbase function

   $ Bash example

   # Install R if not already installed (example for Debian/Ubuntu)
   # sudo apt-get update && sudo apt-get install -y r-base
   
   # Assuming input data is in a tab-separated file (input.tsv)
   # and intensity values are in a column named 'Intensity'.
   # This script will add a new column 'Intensity_log2'.
   
   # Create a dummy input file for demonstration (replace with your actual input.tsv)
   # echo -e "Sample\tIntensity\tOtherData" > input.tsv
   # echo -e "S1\t100\tA" >> input.tsv
   # echo -e "S2\t250\tB" >> input.tsv
   # echo -e "S3\t50\tC" >> input.tsv
   # echo -e "S4\t1000\tD" >> input.tsv
   
   Rscript -e '
     # Read the input data
     data <- read.delim("input.tsv", header = TRUE, sep = "\t")
     
     # Perform log2 transformation on the "Intensity" column
     # Ensure the column exists and contains numeric values
     if ("Intensity" %in% colnames(data)) {
       data$Intensity_log2 <- log2(data$Intensity)
     } else {
       stop("Column 'Intensity' not found in the input file.")
     }
     
     # Write the transformed data to a new output file
     write.table(data, "output_log2.tsv", sep = "\t", row.names = FALSE, quote = FALSE)
   '
   
   # To view the output file:
   # cat output_log2.tsv

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