module_FA | R Documentation |
Functional analysis of miRNA sponge modules, including functional enrichment and disease enrichment analysis
module_FA(
Modulelist,
GOont = "BP",
KEGGorganism = "hsa",
Reactomeorganism = "human",
OrgDb = "org.Hs.eg.db",
padjustvaluecutoff = 0.05,
padjustedmethod = "BH",
Analysis.type = c("FEA", "DEA")
)
Modulelist |
List object: a list of miRNA sponge modules. |
GOont |
One of 'MF', 'BP', and 'CC' subontologies. |
KEGGorganism |
Organism, supported organism listed in http://www.genome.jp/kegg/catalog/org_list.html. |
Reactomeorganism |
Organism, one of 'human', 'rat', ' mouse', 'celegans', 'yeast', 'zebrafish', 'fly'. |
OrgDb |
OrgDb |
padjustvaluecutoff |
A cutoff value of adjusted p-values. |
padjustedmethod |
Adjusted method of p-values, can select one of 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none'. |
Analysis.type |
The type of functional analysis selected, including 'FEA' (functional enrichment analysis) and 'DEA' (disease enrichment analysis). |
List object: a list of enrichment analysis results.
Junpeng Zhang (https://www.researchgate.net/profile/Junpeng-Zhang-2)
Zhang J, Liu L, Xu T, Xie Y, Zhao C, Li J, Le TD (2019). “miRspongeR: an R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules.” BMC Bioinformatics, 20, 235.
Zhang J, Liu L, Zhang W, Li X, Zhao C, Li S, Li J, Le TD. miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation. Bioinform Adv. 2022 Sep 2;2(1):vbac063.
Yu G, Wang L, Han Y, He Q (2012). “clusterProfiler: an R package for comparing biological themes among gene clusters.” OMICS: A Journal of Integrative Biology, 16(5), 284-287.
## Not run:
data(BRCASampleData)
modulegenes_WGCNA <- module_WGCNA(ceRExp, mRExp)
# Identify miRNA sponge modules using sensitivity RV coefficient (SRVC)
miRSM_WGCNA_SRVC <- miRSM(miRExp, ceRExp, mRExp, miRTarget,
modulegenes_WGCNA, method = "SRVC",
SMC.cutoff = 0.01, RV_method = "RV")
miRSM_WGCNA_SRVC_genes <- miRSM_WGCNA_SRVC[[2]]
miRSM_WGCNA_SRVC_FEA <- module_FA(miRSM_WGCNA_SRVC_genes, Analysis.type = 'FEA')
miRSM_WGCNA_SRVC_DEA <- module_FA(miRSM_WGCNA_SRVC_genes, Analysis.type = 'DEA')
## End(Not run)
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