GSE77699 Processing Pipeline

Publication

Nature communications (2016) — PMID 27378374

Dataset

Distinct and shared functions of ALS-associated TDP-43, FUS, and TAF15 revealed by comprehensive multi-system integrative analyses [array]

1. 1

   Data processed using Affymetrix package (Affy Power Tools) apt-probeset-summarize.

   Microarray vInferred with models/gemini-2.5-flash

   $ Bash example

   # Affymetrix Power Tools (APT) is typically downloaded from the Thermo Fisher Scientific website or installed via a package manager like Bioconda.
   # conda install -c bioconda affymetrix-power-tools
   
   # Example usage of apt-probeset-summarize. 
   # Replace 'input_cel_file_1.cel', 'input_cel_file_2.cel' with actual CEL file paths.
   # Replace 'annotation.cdf' with the appropriate CDF file for your array type.
   # Replace 'output_summaries' with your desired output directory.
   
   apt-probeset-summarize \
       --cel-files input_cel_file_1.cel,input_cel_file_2.cel \
       --cdf-file annotation.cdf \
       --output-dir output_summaries \
       --log-file output_summaries/apt_summarize.log

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2. 2

   Iter-plier algorithm used to quantify probesets.

   iterplieR (Inferred with models/gemini-2.5-flash) v1.20.0

   $ Bash example

   # Install R and Bioconductor if not already installed
   # For example, on Ubuntu:
   # sudo apt-get update
   # sudo apt-get install r-base
   # R -e 'if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager"); BiocManager::install("iterplieR")'
   # R -e 'if (!requireNamespace("affy", quietly = TRUE)) BiocManager::install("affy")'
   
   # Example R script to quantify probesets using iterplieR
   # Save this content to a file, e.g., quantify_probesets.R
   cat << 'EOF' > quantify_probesets.R
   # Load the iterplieR package and affy for reading CEL files
   library(iterplieR)
   library(affy)
   
   # --- Configuration ---
   # Define the path to your CEL files
   # IMPORTANT: Replace './cel_files' with the actual path to your Affymetrix .CEL files
   cel_files_dir <- "./cel_files"
   # Define the output directory
   output_dir <- "./quantified_data"
   dir.create(output_dir, showWarnings = FALSE)
   
   # --- Main Workflow ---
   # 1. Read CEL files
   # This assumes you have .CEL files in the 'cel_files_dir'
   # You might need to adjust this based on your specific data structure or chip type.
   # For example, if you have a specific CDF package installed (e.g., hgu133plus2cdf):
   # library(hgu133plus2cdf)
   # affy_batch <- ReadAffy(filenames = cel_files, cdfname = "hgu133plus2cdf")
   
   cel_files <- list.files(path = cel_files_dir, pattern = "\\.CEL$", full.names = TRUE, ignore.case = TRUE)
   if (length(cel_files) == 0) {
     stop("No .CEL files found in the specified directory: ", cel_files_dir)
   }
   message(paste("Found", length(cel_files), ".CEL files."))
   affy_batch <- ReadAffy(filenames = cel_files)
   
   # 2. Apply Iter-plier algorithm
   # The iterplieR function takes an AffyBatch object
   # and returns a matrix of probeset intensities.
   message("Applying Iter-plier algorithm...")
   iterplier_results <- iterplieR(affy_batch)
   
   # 3. Extract and save quantified probeset data
   # The result is a matrix where rows are probesets and columns are samples.
   output_file <- file.path(output_dir, "iterplier_quantified_probesets.tsv")
   write.table(iterplier_results, file = output_file, sep = "\t", quote = FALSE, row.names = TRUE)
   
   message(paste("Quantification complete. Results saved to:", output_file))
   EOF
   
   # Execute the R script
   Rscript quantify_probesets.R

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Tools Used