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Article details
Title
RCPA: An Open‐Source R Package for Data Processing, Differential Analysis, Consensus Pathway Analysis, and Visualization
Published in
Current Protocols, May 2024
DOI 10.1002/cpz1.1036
Pubmed ID
Authors
Abstract

Identifying impacted pathways is important because it provides insights into the biology underlying conditions beyond the detection of differentially expressed genes. Because of the importance of such analysis, more than 100 pathway analysis methods have been developed thus far. Despite the availability of many methods, it is challenging for biomedical researchers to learn and properly perform pathway analysis. First, the sheer number of methods makes it challenging to learn and choose the correct method for a given experiment. Second, computational methods require users to be savvy with coding syntax, and comfortable with command-line environments, areas that are unfamiliar to most life scientists. Third, as learning tools and computational methods are typically implemented only for a few species (i.e., human and some model organisms), it is difficult to perform pathway analysis on other species that are not included in many of the current pathway analysis tools. Finally, existing pathway tools do not allow researchers to combine, compare, and contrast the results of different methods and experiments for both hypothesis testing and analysis purposes. To address these challenges, we developed an open-source R package for Consensus Pathway Analysis (RCPA) that allows researchers to conveniently: (1) download and process data from NCBI GEO; (2) perform differential analysis using established techniques developed for both microarray and sequencing data; (3) perform both gene set enrichment, as well as topology-based pathway analysis using different methods that seek to answer different research hypotheses; (4) combine methods and datasets to find consensus results; and (5) visualize analysis results and explore significantly impacted pathways across multiple analyses. This protocol provides many example code snippets with detailed explanations and supports the analysis of more than 1000 species, two pathway databases, three differential analysis techniques, eight pathway analysis tools, six meta-analysis methods, and two consensus analysis techniques. The package is freely available on the CRAN repository. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing Affymetrix microarrays Basic Protocol 2: Processing Agilent microarrays Support Protocol: Processing RNA sequencing (RNA-Seq) data Basic Protocol 3: Differential analysis of microarray data (Affymetrix and Agilent) Basic Protocol 4: Differential analysis of RNA-Seq data Basic Protocol 5: Gene set enrichment analysis Basic Protocol 6: Topology-based (TB) pathway analysis Basic Protocol 7: Data integration and visualization.

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Mendeley demographics

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The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Unspecified 2 18%
Student > Bachelor 1 9%
Researcher 1 9%
Other 1 9%
Unknown 6 55%
Readers by discipline
Readers by discipline Count As %
Unspecified 2 18%
Biochemistry, Genetics and Molecular Biology 2 18%
Agricultural and Biological Sciences 1 9%
Unknown 6 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 May 2024.
All research outputs
#21,074,934
of 25,885,333 outputs
Outputs from Current Protocols
#547
of 662 outputs
Outputs of similar age
#106,634
of 159,275 outputs
Outputs of similar age from Current Protocols
#7
of 9 outputs
Altmetric has tracked 25,885,333 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 662 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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