| Title: | Gene set collections for the EGSEA package |
|---|---|
| Description: | This package includes gene set collections that are used for the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. It includes Human and Mouse versions of the MSidDB (Subramanian, et al. (2005) PNAS, 102(43):15545-15550) and GeneSetDB (Araki, et al. (2012) FEBS Open Bio, 2:76-82) collections. |
| Authors: | Monther Alhamdoosh, Yifang Hu and Gordon K. Smyth |
| Maintainer: | Monther Alhamdoosh <[email protected]> |
| License: | file LICENSE |
| Version: | 1.41.0 |
| Built: | 2026-10-10 10:41:32 UTC |
| Source: | https://github.com/bioc/EGSEAdata |
This package includes gene set collections that are used for the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. It includes Human and Mouse versions of the MSidDB (Subramanian, et al. (2005) PNAS, 102(43):15545-15550) and GeneSetDB (Araki, et al. (2012) FEBS Open Bio, 2:76-82) collections.
While the gene set collections in MSigDB and GeneSetDB have different names and purposes, some of these collections overlap. For example, both databases contain a Gene Ontology collection but MSigDB's collection aimed for a higher level of abstraction for the GO terms.
Monther Alhamdoosh, Yifang Hu and Gordon K. Smyth
Monther Alhamdoosh, Milica Ng, Nicholas J. Wilson, Julie M. Sheridan, Huy Huynh, Michael J. Wilson, Matthew E. Ritchie; Combining multiple tools outperforms individual methods in gene set enrichment analyses. Bioinformatics 2017; 33 (3): 414-424. doi: 10.1093/bioinformatics/btw623
It displays information about the available gene set collections in EGSEAdata for a species.
egsea.data(species = "human", simple = FALSE, returnInfo = FALSE)egsea.data(species = "human", simple = FALSE, returnInfo = FALSE)
species |
character, a species name and used to retreive the number of gene sets for that particular species. Default is "human". Accepted values are "human", "homo sapiens", "hs", "mouse", "mus musculus", "mm", "rat", "rattus norvegicus" or "rn". |
simple |
logical, whether to display the number of gene sets in each collection or not. |
returnInfo |
logical, whether to print out the databases information or return it as a list. |
It prints out for each database: the database name, version, update/download date, data source, supported species, gene set collections, the names of the related R data objects and the number of gene sets in each collection.
nothing.
# Example of egsea.data egsea.data()# Example of egsea.data egsea.data()
Human gene set collections from the GeneSetDB
list
Procedure
1. The Human GMT file was downloaded from the website.
2. The gene set sources and categories were manually compiled from the Help page.
3. An R list was created for the gene set categories.
4. An annotation data frame was created for the gene sets.
5. An R data object was written using save().
Araki Hiromitsu,Knapp Christoph,Tsai Peter and Print Cristin(2012), GeneSetDB: A comprehensive meta-database, statistical and visualisation framework for gene set analysis, FEBS Open Bio, 2, doi: 10.1016/j.fob.2012.04.003 Downloaded from http://www.genesetdb.auckland.ac.nz/
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse gene set collections from the GeneSetDB
list
Procedure
1. The Mouse GMT file was downloaded from the website.
2. The gene set sources and categories were manually compiled from the Help page.
3. An R list was created for the gene set categories.
4. An annotation data frame was created for the gene sets.
5. An R data object was written using save().
Araki Hiromitsu,Knapp Christoph,Tsai Peter and Print Cristin(2012), GeneSetDB: A comprehensive meta-database, statistical and visualisation framework for gene set analysis, FEBS Open Bio, 2, doi: 10.1016/j.fob.2012.04.003 Downloaded from http://www.genesetdb.auckland.ac.nz/
Invoke egsea.data() to find out the current version and latest download/update date.
Rat gene set collections from the GeneSetDB
list
Procedure
1. The Rat GMT file was downloaded from the website.
2. The gene set sources and categories were manually compiled from the Help page.
3. An R list was created for the gene set categories.
4. An annotation data frame was created for the gene sets.
5. An R data object was written using save().
Araki Hiromitsu,Knapp Christoph,Tsai Peter and Print Cristin(2012), GeneSetDB: A comprehensive meta-database, statistical and visualisation framework for gene set analysis, FEBS Open Bio, 2, doi: 10.1016/j.fob.2012.04.003 Downloaded from http://www.genesetdb.auckland.ac.nz/
Invoke egsea.data() to find out the current version and latest download/update date.
The voom object calculated from the TMM normalized count matrix of RNA-seq performed on samples of human normal PBMCs, IL-13 stimulated PBMCs and IL-13R antagnonist PBBMCs. It also contains the contrast matrix of this experiment.
A List object with two components: voom and contra.
The count matrix of this experiment is vailable from the GEO database www.ncbi.nlm.nih.gov/geo/ as series GSE79027.
It contains the raw count matrix of RNA-seq performed on samples of human normal PBMCs, IL-13 stimulated PBMCs and IL-13R antagnonist PBBMCs. It also contains the contrast and design matrices of this experiment. The gene symbols mapping is also included.
A List object with five components: counts, group, design, contra and genes.
The FASTQ files of this experiment are vailable from the GEO database www.ncbi.nlm.nih.gov/geo/ as series GSE79027.
EGSEA analysis was performed on the il13.data from the EGSEAdata package using the KEGG pathways, c2 and c5 gene set collections. Type show(il13.gsa) to see the version of datasets/packages that were used.
An object of class EGSEAResults
The dataset of this analysis is available in the EGSEAdata package.
Human, Mouse and Rat gene set collections from the KEGG database
list
The collections were generated using the following R script
library(gage)
kegg.pathways = list()
species.all = c("human", "mouse", "rat")
for (species in species.all)
kegg = kegg.gsets(species = species, id.type = "kegg")
kegg.pathways[[species]] = kegg
save(kegg.pathways, file='kegg.pathways.rda')
Luo, W., Friedman, M., Shedden K., Hankenson, K. and Woolf, P GAGE: Generally Applicable
Gene Set Enrichment for Pathways Analysis. BMC Bioinformatics 2009, 10:161
Obtained from gage using the function kegg.gsets()
Invoke egsea.data() to find out the current version and latest download/update date.
The voom object calculated from TMM normalized count matrix of RNA-seq performed on samples of the epithelial cells of the mouse mammary glands from three populations: basal, luminal progenitor and mature luminal. It also contains the contrast matrix of this experiment.
A List object with two components: voom and contra.
The count matrix of this experiment is vailable from the GEO database www.ncbi.nlm.nih.gov/geo/ as series GSE63310.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/ Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Mouse orthologs gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. Human Entrez Gene IDs were mapped to Mouse Entrez Gene IDs, using the HGNC
Comparison of Orthology Predictions (HCOP).
3. The collection was converted to a list in R, and written to a RData file using save().
Downloaded from http://bioinf.wehi.edu.au/software/MSigDB/. Extracted from Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.
Gene set collections from the MSigDB database
list
Procedure
1. The current msigdb_vx.xml file was downloaded.
2. It was parsed using xmlParse() and then converted to list using xmlToList()
3. The resulting list was written to an RData file using save().
This dataset is mainly used to extract MSigDB gene set annotation and the human gene set
collections.
Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Sayan Mukherjee, Benjamin L. Ebert, Michael A. Gillette, Amanda Paulovich, Scott L. Pomeroy, Todd R. Golub, Eric S. Lander, and Jill P. Mesirov Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles PNAS 2005 102 (43) 15545-15550
Invoke egsea.data() to find out the current version and latest download/update date.