GSE86462 Processing Pipeline

Publication

Neuron (2016) — PMID 27773581

Dataset

HNRNPA2B1 regulates alternative RNA processing in the nervous system and accumulates in granules in ALS IPSC-derived motor neurons [hnRNPA2B1_Arrays_…

1. 1

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

   Microarray vNot specified (Inferred with models/gemini-2.5-flash)

   $ Bash example

   # Install Affymetrix Power Tools (APT) via Bioconda
   # conda install -c bioconda affy-power-tools
   
   # Example usage of apt-probeset-summarize
   # This command processes raw Affymetrix CEL files to generate probe set summaries.
   # Replace <array_type_library_file>, <output_directory>, <probeset_file>, and <cel_file(s)> with actual paths.
   # The array type library file (.pgf, .clf, .qcc) and probeset file (.mps) are specific to the Affymetrix array used.
   # Common summarization algorithms include RMA (Robust Multi-array Average), MAS5, PLIER.
   # The specific algorithm can be chosen using options like --rma, --mas5, --plier.
   # For example, using RMA:
   apt-probeset-summarize --log-file apt_summarize.log --cel-files <path/to/cel_file1.CEL> <path/to/cel_file2.CEL> --out-dir <output_directory> --analysis-files-path <path/to/library_files_directory> --set-analysis-algorithm rma
   # Or, if using a list of CEL files:
   # apt-probeset-summarize --log-file apt_summarize.log --cel-file-list <path/to/cel_file_list.txt> --out-dir <output_directory> --analysis-files-path <path/to/library_files_directory> --set-analysis-algorithm rma
   # Note: <path/to/library_files_directory> should contain the .pgf, .clf, .qcc, .mps files for your array type.
   # The output will typically be a .chp file and a text file with expression values.

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2. 2

   Iter-plier algorithm used to quantify probesets.

   affy (R package) (Inferred with models/gemini-2.5-flash) v1.80.0 (Inferred with models/gemini-2.5-flash)

   $ Bash example

   # Install R and Bioconductor if not already installed
   # For Bioconductor 3.19 (R 4.4):
   # R -e 'if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")'
   # R -e 'BiocManager::install("affy")'
   
   # Define input directory containing .CEL files
   CEL_DIR="path/to/your/cel_files"
   OUTPUT_FILE="probeset_quantification.txt"
   
   # Create an R script to perform PLIER quantification
   cat <<EOF > run_plier.R
   library(affy)
   
   # Get list of CEL files
   cel_files <- list.files("${CEL_DIR}", pattern = "\\.CEL$", full.names = TRUE)
   
   if (length(cel_files) == 0) {
     stop("No .CEL files found in ${CEL_DIR}")
   }
   
   # Read CEL files
   raw_data <- ReadAffy(filenames = cel_files)
   
   # Perform PLIER summarization
   # The 'just.plier' function performs background correction, normalization, and summarization
   eset_plier <- just.plier(raw_data)
   
   # Extract expression matrix
   expression_matrix <- exprs(eset_plier)
   
   # Write the expression matrix to a tab-separated file
   write.table(expression_matrix, file = "${OUTPUT_FILE}", sep = "\t", quote = FALSE, col.names = NA)
   
   message(paste0("Probeset quantification completed and saved to ${OUTPUT_FILE}"))
   EOF
   
   # Execute the R script
   Rscript run_plier.R
   
   # Clean up the R script
   rm run_plier.R

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3. 3

   HTA-2_0.r3.pgf

   Affymetrix Power Tools (APT) (Inferred with models/gemini-2.5-flash) vNot explicitly stated.

   $ Bash example

   # Install Affymetrix Power Tools (APT) if not already installed.
   # APT binaries can be downloaded from the Thermo Fisher Scientific website.
   # Example installation (conceptual, as exact steps vary by OS and APT version):
   # wget https://assets.thermofisher.com/TFS-Assets/LSG/software/APT_2.11.2_Linux_x86_64.zip
   # unzip APT_2.11.2_Linux_x86_64.zip
   # export PATH=$PATH:/path/to/APT_binaries
   
   # Define input and output files/directories
   PGF_FILE="HTA-2_0.r3.pgf" # Probe Group File for Human Transcriptome Array 2.0
   CDF_FILE="HTA-2_0.r3.cdf" # Chip Description File, often accompanies the PGF file
   CEL_FILES="sample1.CEL sample2.CEL sample3.CEL" # Placeholder for input raw CEL files from the array
   OUTPUT_DIR="summarized_hta_data"
   ANALYSIS_PROTOCOL="rma" # Robust Multi-array Average is a common summarization method
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Execute the probeset summarization using APT's apt-probeset-summarize command.
   # This command performs background correction, normalization, and summarization
   # of probe-level data from CEL files into expression values.
   apt-probeset-summarize \
     --pgf-file "${PGF_FILE}" \
     --cdf-file "${CDF_FILE}" \
     --cel-files "${CEL_FILES}" \
     --output-dir "${OUTPUT_DIR}" \
     --analysis-protocol "${ANALYSIS_PROTOCOL}" \
     --log-file "${OUTPUT_DIR}/apt_summarize.log"
   

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Tools Used