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Data from: Differential Expression Analysis for Pathways

Haynes, Winston A., Bioinformatics & High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, Washington, United States of America
Higdon, Roger, Bioinformatics & High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, Washington, United States of America
Stanberry, Larissa, Bioinformatics & High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, Washington, United States of America
Collins, Dwayne, Conway School of Landscape Design
Kolker, Eugene, Washington University School of Medicine
Published Mar 28, 2013 on Dryad. https://doi.org/10.5061/dryad.qh1pg

Cite this dataset

Haynes, Winston A. et al. (2013). Data from: Differential Expression Analysis for Pathways [Dataset]. Dryad. https://doi.org/10.5061/dryad.qh1pg

Abstract

Life science technologies generate a deluge of data that hold the keys to unlocking the secrets of important biological functions and disease mechanisms. We present DEAP, Differential Expression Analysis for Pathways, which capitalizes on information about biological pathways to identify important regulatory patterns from differential expression data. DEAP makes significant improvements over existing approaches by including information about pathway structure and discovering the most differentially expressed portion of the pathway. On simulated data, DEAP significantly outperformed traditional methods: with high differential expression, DEAP increased power by two orders of magnitude; with very low differential expression, DEAP doubled the power. DEAP performance was illustrated on two different gene and protein expression studies. DEAP discovered fourteen important pathways related to chronic obstructive pulmonary disease and interferon treatment that existing approaches omitted. On the interferon study, DEAP guided focus towards a four protein path within the 26 protein Notch signalling pathway.

Usage notes

DEAP Validation 1: Pathway Data

Representations of the simulated pathways from the section "DEAP Validation 1: Simulated Data on Simulated Pathways" in the *.edg format utilized for input into the DEAP algorithm.
Validation1_PathwayData.tar.gz

DEAP Validation 1: Expression Data

All simulated expression data used for the section "DEAP Validation 1: Simulated Data on Simulated Pathways". Data is in the TSV format used for input into the DEAP algorithm. Simulated data was generated as described in "Methods: Simulated Data". File naming indicates the variables input into the simulation algorithm.
Validation1_ExpressionData.tar.gz

DEAP Validation 2: Pathway Data

Representations of the simulated pathways from the section "DEAP Validation 2: Simulated Data on Biological Pathways" in the *.edg format utilized for input into the DEAP algorithm.
Validation2_PathwayData.tar.gz

DEAP Validation 2: Expression Data Part 1

All simulated expression data used for the section "DEAP Validation 2: Simulated Data on Biological Pathways". Data is in the TSV format used for input into the DEAP algorithm. Simulated data was generated as described in "Methods: Simulated Data". File naming indicates the variables input into the simulation algorithm.
Validation2_ExpressionData_Part1.tar.gz

DEAP Validation 2: Expression Data Part 2

All simulated expression data used for the section "DEAP Validation 2: Simulated Data on Biological Pathways". Data is in the TSV format used for input into the DEAP algorithm. Simulated data was generated as described in "Methods: Simulated Data". File naming indicates the variables input into the simulation algorithm.
Validation2_ExpressionData_Part2.tar.gz