| Title: | Enrichment Approach to Predict Which Transcription Factors are Regulated |
|---|---|
| Description: | R implementation of 'TFactS' to predict which are the transcription factors (TFs), regulated in a biological condition based on lists of differentially expressed genes (DEGs) obtained from transcriptome experiments. This package is based on the 'TFactS' concept by Essaghir et al. (2010) <doi:10.1093/nar/gkq149> and expands it. It allows users to perform 'TFactS'-like enrichment approach. The package can import and use the original catalogue file from the 'TFactS' as well as users' defined catalogues of interest that are not supported by 'TFactS' (e.g., Arabidopsis). |
| Authors: | Atsushi Fukushima [aut, cre] |
| Maintainer: | Atsushi Fukushima <[email protected]> |
| License: | GPL-3 |
| Version: | 0.99.1 |
| Built: | 2024-11-25 05:40:07 UTC |
| Source: | https://github.com/afukushima/tfactsr |
A catalogue of annotated target genes in Arabidopsis thaliana based on ATRM
The original regulatory network datasets were downloaded from ATRM (http://atrm.cbi.pku.edu.cn/).
None
Jin JP et al. Mol Bio Evol 32:1767-1773 (2015)
This function performs enrichment test (ET) based on Fisher's exact test
calculateEnrichmentTest( DEGs, catalog, TFs, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )calculateEnrichmentTest( DEGs, catalog, TFs, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )
DEGs |
a character vector of DEGs (differentially expressed genes) |
catalog |
a data frame of TFactS catalog (ver. 2) |
TFs |
a character vector of transcription factor |
TF.col |
the name of the column that contains the TF names |
TG.col |
the name of the column that contains the TG names |
data.frame
Atsushi Fukushima Definition: m is the number of target genes annotated for the TF under consideration n is the number of query genes N is the number of regulations in the catalog k is the number of query genes that are annotated as regulated by TF (i.e., the intersection between the query and the TF signature)
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs res <- calculateEnrichmentTest(DEGs, catalog, TFs)data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs res <- calculateEnrichmentTest(DEGs, catalog, TFs)
This function calculates E-value based on .
calculateEvalue(df, TFs)calculateEvalue(df, TFs)
df |
a data frame containng p-values |
TFs |
a character vector of transcription factor |
data.frame
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs p.value <- runif(10)/(1:10) df <- data.frame(p.value = p.value) res <- calculateEvalue(df, TFs)data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs p.value <- runif(10)/(1:10) df <- data.frame(p.value = p.value) res <- calculateEvalue(df, TFs)
This function calculates FDR based on BH.
calculateFDRBH(df)calculateFDRBH(df)
df |
a data frame containng p-values |
data.frame
Atsushi Fukushima
Benjamini Y and Hochberg Y, J Roy Stat Soc B 57: 289?300 (1995)
p.value <- runif(10)/(1:10) df <- data.frame(p.value = p.value) res <- calculateFDRBH(df)p.value <- runif(10)/(1:10) df <- data.frame(p.value = p.value) res <- calculateFDRBH(df)
This function calculates Q-value based on Storey.
calculateQvalue(df, lambda = seq(0.05, 0.5, 0.01))calculateQvalue(df, lambda = seq(0.05, 0.5, 0.01))
df |
a data frame containng p-values |
lambda |
a vector of the lambda values utilized to obtain pi0.lambda |
data.frame
Atsushi Fukushima
Storey JD, The Annals of Statistics 31:2013-2035 (2003)
data(example.df) p.value <- example.df$p.value df <- data.frame(p.value = p.value) res <- calculateQvalue(df)data(example.df) p.value <- example.df$p.value df <- data.frame(p.value = p.value) res <- calculateQvalue(df)
This function calculates Random Control (RC)
calculateRC( df, DEGs, catalog, TFs, all.targets, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", lambda = 0.05, nRep = 100 )calculateRC( df, DEGs, catalog, TFs, all.targets, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", lambda = 0.05, nRep = 100 )
df |
a data frame containng p-values |
DEGs |
a character vector of DEGs (differentially expressed genes) |
catalog |
a data frame of TFactS catalog (ver. 2) |
TFs |
a character vector of transcription factor |
all.targets |
a character vector of all target genes |
TF.col |
the name of the column that contains the TF names |
lambda |
a user-specified threshold of E-value (default: 0.05) |
nRep |
number of random selections (default: 100) |
data.frame
Atsushi Fukushima Definition: m is the number of target genes annotated for the TF under consideration n is the number of query genes N is the number of regulations in the catalog k is the number of query genes that are annotated as regulated by TF (i.e., the intersection between the query and the TF signature)
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
data(example.df) data(catalog) data(DEGs) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- calculateRC(example.df, DEGs, catalog, TFs, all.targets)data(example.df) data(catalog) data(DEGs) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- calculateRC(example.df, DEGs, catalog, TFs, all.targets)
This function calculates TFactS
calculateTFactS( DEGs, catalog, TFs, all.targets, Q.value = FALSE, lambda1 = seq(0.05, 0.5, 0.01), lambda2 = 0.05, nRep = 100, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )calculateTFactS( DEGs, catalog, TFs, all.targets, Q.value = FALSE, lambda1 = seq(0.05, 0.5, 0.01), lambda2 = 0.05, nRep = 100, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )
DEGs |
a character vector of DEGs (differentially expressed genes) |
catalog |
a data frame of TFactS catalog (ver. 2) |
TFs |
a character vector of transcription factor |
all.targets |
a character vector of all target genes |
Q.value |
logical. If it is TRUE, Q.value by Storey method. |
lambda1 |
a vector of the lambda values utilized to obtain pi0.lambda |
lambda2 |
a user-specified threshold of E-value (default: 0.05) |
nRep |
number of random selections (default: 100) |
TF.col |
the name of the column that contains the TF names |
TG.col |
the name of the column that contains the TG names |
data.frame
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- calculateTFactS(DEGs, catalog, TFs, all.targets)data(DEGs) data(catalog) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- calculateTFactS(DEGs, catalog, TFs, all.targets)
A catalogue of annotated target genes based on TFactS.
This was downloaded from TFactS (http://www.tfacts.org/).
The catalogues version is 2 (http://www.tfacts.org/TFactS-new/TFactS-v2/tfacts/data/Catalogues.xls).
None
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
An example list of differentially expressed genes (DEGs).
This was from DEMO data in TFactS (http://www.tfacts.org/). The list corresponds to 18 up-regulated genes.
None
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
A list of 39 differentially expressed genes (DEGs).
This was from DEMO data in TFactS (http://www.tfacts.org/). The list corresponds to 18 up-regulated genes and 21 down-regulated genes.
None
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
An example result of enrichment analysis
The size of data frame is 345 TFs and 6 columns.
None
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
An example list of result of enrichment analysis
The length of the list is 345 (TFs).
None
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
This function extracts information about transcription factor (TF) and target gene (TG) with TFactS Catalogue (v2).
extractTFTG( DEGs, catalog, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )extractTFTG( DEGs, catalog, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", TG.col = "Target.gene..OFFICIAL_GENE_NAME." )
DEGs |
a character vector of DEGs (differentially expressed genes) |
catalog |
a data frame of TFactS catalog (ver. 2) |
TF.col |
the name of the column that contains the TF names |
TG.col |
the name of the column that contains the TG names |
list
Atsushi Fukushima
data(DEGs) data(catalog) res <- extractTFTG(DEGs, catalog) head(res$TFs)data(DEGs) data(catalog) res <- extractTFTG(DEGs, catalog) head(res$TFs)
This function calculates Random Control (RC)
FASTcalculateRC( df, DEGs, catalog, TFs, all.targets, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", lambda = 0.05, nRep = 100 )FASTcalculateRC( df, DEGs, catalog, TFs, all.targets, TF.col = "TF..OFFICIAL_TF_CODING_GENE_NAME.", lambda = 0.05, nRep = 100 )
df |
a data frame containng p-values |
DEGs |
a character vector of DEGs (differentially expressed genes) |
catalog |
a data frame of TFactS catalog (ver. 2) |
TFs |
a character vector of transcription factor |
all.targets |
a character vector of all target genes |
TF.col |
the name of the column that contains the TF names |
lambda |
a user-specified threshold of E-value (default: 0.05) |
nRep |
number of random selections (default: 100) |
data.frame
Atsushi Fukushima
Essaghir A et al. Nucleic Acids Res. 2010 Jun;38(11):e120.
data(example.df) data(catalog) data(DEGs) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- FASTcalculateRC(example.df, DEGs, catalog, TFs, all.targets)data(example.df) data(catalog) data(DEGs) tftg <- extractTFTG(DEGs, catalog) TFs <- tftg$TFs all.targets <- tftg$all.targets res <- FASTcalculateRC(example.df, DEGs, catalog, TFs, all.targets)
This function formats the result of enrichment test (ET) based on Fisher's exact test
formatET(list)formatET(list)
list |
a list of the result of enrichment test (ncol = 6) |
data.frame
Atsushi Fukushima
data(example.list) res <- formatET(example.list)data(example.list) res <- formatET(example.list)
This function formats the result of Random Control (RC) with random simulation based on Fisher's exact test
formatRC(df, list, nRep)formatRC(df, list, nRep)
df |
a data frame of ET including E-values, FDR-BH, and Q-values |
list |
a list of the result of RC (ncol = 2) |
nRep |
the number of random selections (negative control) |
data.frame
Atsushi Fukushima
data(example.df) data(example.list) nRep <- 100 res <- formatRC(example.df, example.list, nRep)data(example.df) data(example.list) nRep <- 100 res <- formatRC(example.df, example.list, nRep)
A list of 74 differentially expressed genes (DEGs) from AtGenExpress
This was from DEMO data in the Supplemental data (Table S4. Genes regulated by UV-B light stress in roots and shoots; filename: TPJ_3052_sm_TabS4.xls) of the paper by Killian et al. TPJ (2008). The list corresponds to 74 genes up-regulated in roots and shoots 1 hour after onset of UV-B stress treatment.
None
Atsushi Fukushima
Killian J et al. Plant J. 2007 Apr;50(2):347-363.
TFactS is to predict which are the transcription factors (TFs), regulated in a biological condition based on lists of differentially expressed genes (DEGs) obtained from transcriptome experiments. This package is based on the TFactS concept and expands it. It allows users to performe TFactS-like enrichment approach. The package can import and use the original catalogue file from the TFactS website (http://www.tfacts.org/) as well as users' defined catalogues of interest that are not supported by TFactS (e.g., Arabidopsis).