GO-PCA 0.2 User Manual¶
Detail from a GO-PCA signature plot.
This is the user manual for GO-PCA, a free and open-source Python implementation of the eponymous method for exploring gene expression data using prior knowledge.
Contents¶
- Introduction
- Installation
- Obtaining Gene Sets
- Running GO-PCA
- The GO-PCA Python API
- The GO-PCA Command-line interface
- Running GO-PCA:
go-pca.py - Inspecting the results:
gopca_print_info.py - Extracting the signature matrix (as tab-delimited text file):
gopca_extract_signature_matrix.py - Plotting the signature matrix as a heatmap:
gopca_plot_signature_matrix.py - Extracting the signatures (as tab-delimited text file):
gopca_extract_signatures.py - Extracting the signatures (as Excel spreadsheet):
gopca_extract_signatures_excel.py
- Running GO-PCA:
- Citing GO-PCA
- License
Note
This manual uses “GO-PCA”, in italics, to specifically reference the general methodology described in Wagner (2015). In all other cases, “GO-PCA” is meant to reference the Python software documented here.