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Introduction

rChEA3 is an R client for the ChEA3 transcription factor enrichment API.

While ChEA3 is only available online as a web server, rChEA3 provides access to this tool directly in R, streamlining transcription factor enrichment into your workflow. Submit gene lists, retrieve TF rankings from multiple evidence sources (ChIP-seq, co-expression, literature), and integrate results into your R/Bioconductor analysis pipeline.

The package includes convenient functions to query the API, retrieve results across collections, prepare outputs for downstream analysis, and generate publication-ready figures.

Example workflow

This section demonstrates a typical workflow with rChEA3, from submitting a gene list to retrieving transcription factor enrichment results. The examples illustrate how to interact with the ChEA3 API, explore the different collections, and visualize results in a clear, publication-ready format.

We start by loading the package:

library(rChEA3)

1. Submit a gene list

Provide a vector of gene symbols as input. The gene list should consist of HGNC-approved gene symbols, as ChEA3 only accepts these standardized gene identifiers.

genes <- c("TP53", "ESR1", "MYC", "NIPBL", "BRCA1")
results <- queryChEA3(genes)
#> Available results 
#> ────────────────────────────── 
#>   ► Integrated Results
#>     ✔ Mean Rank — Average integrated ranks across libraries
#>         Use <your_result>[["Integrated--meanRank"]]
#>     ✔ Top Rank — Top integrated rank across libraries
#>         Use <your_result>[["Integrated--topRank"]]
#>   ──────────────────── 
#>   ► ChIP-Seq
#>     ✔ ENCODE — Interactions mined from the ENCODE project
#>         Use <your_result>[["ENCODE--ChIP-seq"]]
#>     ✔ ReMap — Interactions mined from the ReMap project
#>         Use <your_result>[["ReMap--ChIP-seq"]]
#>     ✔ Literature — Interactions mined from the literature
#>         Use <your_result>[["Literature--ChIP-seq"]]
#>   ──────────────────── 
#>   ► Coexpression
#>     ✔ ARCHS4 — TF-target coexpression in the ARCHS4 dataset
#>         Use <your_result>[["ARCHS4--Coexpression"]]
#>     ✔ GTEx — TF-target coexpression in the GTEx dataset
#>         Use <your_result>[["GTEx--Coexpression"]]
#>   ──────────────────── 
#>   ► Co-occurrence
#>     ✔ Enrichr — TF-target co-occurrence in Enrichr queries
#>         Use <your_result>[["Enrichr--Queries"]]
#>   ────────────────────

Note: For detailed information about the different ChEA3 collections and their underlying methodology, see Keenan et al., 2019.

2. Inspect top results

The function displayTopN() allows a quick inspection of the results by showing the top transcription factors from each collection. By default, the top 10 transcription factors are displayed without applying thresholds.

displayTopN(results)
#> Top 10 per collection 
#> ────────────────────────────── 
#>   ► Integrated Results
#>     ✔ Mean Rank - Average integrated ranks across libraries
#>          Rank     TF Score
#>             1  ZBED6 15.00
#>             2    PGR 41.25
#>             3    SON 45.50
#>             4 ZBTB21 46.50
#>             5   BPTF 58.50
#>             6   SPEN 58.50
#>             7  SMAD4 69.20
#>             8  ZNF12 78.33
#>             9   ARNT 87.00
#>            10   SAFB 93.00
#> 
#>     ✔ Top Rank - Top integrated rank across libraries
#>          Rank      TF     Score
#>             1 TGIF2LY 0.0006143
#>             2  ZNF800 0.0006223
#>             3   CREB1 0.0007123
#>             4  RHOXF1 0.0012290
#>             5  HIVEP1 0.0012450
#>             6    NFYA 0.0014250
#>             7  ZNF654 0.0018430
#>             8    OSR2 0.0018670
#>             9     SP1 0.0021370
#>            10     BBX 0.0024570
#> 
#>   ──────────────────── 
#>   ► ChIP-Seq
#>     ✔ ENCODE - Interactions mined from the ENCODE project
#>          Rank     TF Scaled Rank               Set_name Intersect FET p-value   FDR
#>             1  CEBPB    0.008475        CEBPB_C2C12_MM9         3    0.009772 0.717
#>             2 ZNF217    0.016950       ZNF217_MCF7_HG19         3    0.012720 0.717
#>             3   CTCF    0.025420        CTCF_HEPG2_HG19         4    0.017380 0.717
#>             4  CEBPD    0.033900        CEBPD_K562_HG19         2    0.018070 0.717
#>             5 ZNF384    0.042370      ZNF384_CH12LX_MM9         3    0.019260 0.717
#>             6   ATF2    0.050850       ATF2_H1HESC_HG19         3    0.021370 0.717
#>             7   RELA    0.059320      RELA_GM12878_HG19         2    0.022770 0.717
#>             8   FLI1    0.067800 FLI1_MEGAKARYOCYTE_MM9         3    0.024120 0.717
#>             9    YY1    0.076270       YY1_GM12892_HG19         2    0.031250 0.717
#>            10   JUND    0.084750       JUND_H1HESC_HG19         3    0.037140 0.717
#>          Odds Ratio
#>               9.358
#>               8.449
#>               5.697
#>              12.580
#>               7.167
#>               6.871
#>              11.080
#>               6.541
#>               9.289
#>               5.463
#> 
#>     ✔ ReMap - Interactions mined from the ReMap project
#>          Rank     TF Scaled Rank Set_name Intersect FET p-value   FDR Odds Ratio
#>             1  CXXC4    0.003367    CXXC4         3     0.01325 0.911      8.314
#>             2   MBD3    0.006734     MBD3         2     0.07561 0.911      5.558
#>             3  KMT2B    0.010100    KMT2B         2     0.07561 0.911      5.558
#>             4   RFX2    0.013470     RFX2         2     0.07569 0.911      5.554
#>             5   MBD4    0.016840     MBD4         2     0.07578 0.911      5.550
#>             6  EOMES    0.020200    EOMES         2     0.07578 0.911      5.550
#>             7   TBXT    0.023570     TBXT         2     0.07604 0.911      5.539
#>             8   XBP1    0.026940     XBP1         2     0.07613 0.911      5.535
#>             9 ZBTB33    0.030300   ZBTB33         2     0.07621 0.911      5.531
#>            10  FOXA1    0.033670    FOXA1         2     0.07621 0.911      5.531
#> 
#>     ✔ Literature - Interactions mined from the literature
#>          Rank     TF Scaled Rank                                              Set_name
#>             1   ESR1    0.006098                     ESR1_15608294_CHIPCHIP_MCF7_HUMAN
#>             2   E2F4    0.012200                   E2F4_17652178_CHIPCHIP_JURKAT_HUMAN
#>             3  BACH1    0.018290              BACH1_22875853_CHIPPCR_HELAANDSCP4_HUMAN
#>             4  PPARD    0.024390                 PPARD_23208498_CHIPSEQ_MDAMB231_HUMAN
#>             5    JUN    0.030490                       JUN_21703547_CHIPSEQ_K562_HUMAN
#>             6   E2F7    0.036590                      E2F7_22180533_CHIPSEQ_HELA_HUMAN
#>             7   CUX1    0.042680 CUX1_19635798_CHIPCHIP_MULTIPLEHUMANCANCERTYPES_HUMAN
#>             8  NANOG    0.048780                    NANOG_18347094_CHIPCHIP_MESC_MOUSE
#>             9 POU3F1    0.054880                     POU3F1_26484290_CHIPSEQ_ESC_MOUSE
#>            10   EGR1    0.060980                     EGR1_19374776_CHIPCHIP_THP1_HUMAN
#>          Intersect FET p-value   FDR Odds Ratio
#>                  2    0.000384 0.118     94.090
#>                  3    0.003138 0.482     14.330
#>                  3    0.010030 0.494      9.264
#>                  2    0.010610 0.494     16.770
#>                  3    0.013300 0.494      8.302
#>                  1    0.013400 0.494     90.890
#>                  4    0.016600 0.494      5.783
#>                  3    0.016690 0.494      7.588
#>                  3    0.019720 0.494      7.099
#>                  1    0.019870 0.494     60.590
#> 
#>   ──────────────────── 
#>   ► Coexpression
#>     ✔ ARCHS4 - TF-target coexpression in the ARCHS4 dataset
#>          Rank      TF Scaled Rank               Set_name Intersect FET p-value FDR
#>             1 TGIF2LY   0.0006143 TGIF2LY_ARCHS4_PEARSON         2    0.004325   1
#>             2  RHOXF1   0.0012290  RHOXF1_ARCHS4_PEARSON         2    0.004352   1
#>             3  ZNF654   0.0018430  ZNF654_ARCHS4_PEARSON         1    0.084660   1
#>             4     BBX   0.0024570     BBX_ARCHS4_PEARSON         1    0.084660   1
#>             5  ZNF407   0.0030710  ZNF407_ARCHS4_PEARSON         1    0.084660   1
#>             6     RLF   0.0036860     RLF_ARCHS4_PEARSON         1    0.084660   1
#>             7  ZNF552   0.0043000  ZNF552_ARCHS4_PEARSON         1    0.084660   1
#>             8     YY2   0.0049140     YY2_ARCHS4_PEARSON         1    0.084660   1
#>             9    REST   0.0055280    REST_ARCHS4_PEARSON         1    0.084660   1
#>            10  ZBTB24   0.0061430  ZBTB24_ARCHS4_PEARSON         1    0.084930   1
#>          Odds Ratio
#>               26.93
#>               26.84
#>               13.51
#>               13.51
#>               13.51
#>               13.51
#>               13.51
#>               13.51
#>               13.51
#>               13.46
#> 
#>     ✔ GTEx - TF-target coexpression in the GTEx dataset
#>          Rank      TF Scaled Rank Set_name Intersect FET p-value   FDR Odds Ratio
#>             1  ZNF800   0.0006223   ZNF800         3   0.0001677 0.136      40.53
#>             2  HIVEP1   0.0012450   HIVEP1         3   0.0001694 0.136      40.39
#>             3    OSR2   0.0018670     OSR2         2   0.0042690 0.538      27.11
#>             4   ADNP2   0.0024890    ADNP2         2   0.0043250 0.538      26.93
#>             5   NCOA3   0.0031110    NCOA3         2   0.0043520 0.538      26.84
#>             6 ZSCAN25   0.0037340  ZSCAN25         2   0.0043520 0.538      26.84
#>             7  ZNF317   0.0043560   ZNF317         2   0.0043520 0.538      26.84
#>             8   KLF11   0.0049780    KLF11         2   0.0043520 0.538      26.84
#>             9 ZNF705E   0.0056000  ZNF705E         2   0.0043520 0.538      26.84
#>            10     SP1   0.0062230      SP1         2   0.0043520 0.538      26.84
#> 
#>   ──────────────────── 
#>   ► Co-occurrence
#>     ✔ Enrichr - TF-target co-occurrence in Enrichr queries
#>          Rank    TF Scaled Rank Set_name Intersect FET p-value      FDR Odds Ratio
#>             1 CREB1   0.0007123    CREB1         5   1.539e-07 4.39e-05      68.48
#>             2  NFYA   0.0014250     NFYA         5   1.539e-07 4.39e-05      68.48
#>             3   SP1   0.0021370      SP1         5   1.565e-07 4.39e-05      68.24
#>             4 SMAD4   0.0028490    SMAD4         5   1.565e-07 4.39e-05      68.24
#>             5  ATF2   0.0035610     ATF2         5   1.565e-07 4.39e-05      68.24
#>             6   SRY   0.0042740      SRY         4   5.135e-06 2.57e-04      55.16
#>             7 MYOD1   0.0049860    MYOD1         4   5.204e-06 2.57e-04      54.97
#>             8    AR   0.0056980       AR         4   5.204e-06 2.57e-04      54.97
#>             9   CRX   0.0064100      CRX         4   5.204e-06 2.57e-04      54.97
#>            10 NR5A1   0.0071230    NR5A1         4   5.204e-06 2.57e-04      54.97
#> 
#>   ────────────────────

3. Extract the result for one particular collection

Each ChEA3 collection can be accessed by name. For example, to retrieve the integrated ranking:

meanRank_results <- results[["Integrated--meanRank"]]
head(meanRank_results)
#>     Query Name Rank     TF Score
#> 1 rChEA3_query    1  ZBED6 15.00
#> 2 rChEA3_query    2    PGR 41.25
#> 3 rChEA3_query    3    SON 45.50
#> 4 rChEA3_query    4 ZBTB21 46.50
#> 5 rChEA3_query    5   BPTF 58.50
#> 6 rChEA3_query    6   SPEN 58.50
#>                                                                            Library
#> 1                                                           ARCHS4 Coexpression,15
#> 2 ARCHS4 Coexpression,24;Enrichr Queries,11;ReMap ChIP-seq,84;GTEx Coexpression,46
#> 3                                      ARCHS4 Coexpression,60;GTEx Coexpression,31
#> 4                                      ARCHS4 Coexpression,26;GTEx Coexpression,67
#> 5                                      ARCHS4 Coexpression,68;GTEx Coexpression,49
#> 6                                      ARCHS4 Coexpression,22;GTEx Coexpression,95
#>     Overlapping_Genes
#> 1               NIPBL
#> 2 MYC,BRCA1,ESR1,TP53
#> 3               NIPBL
#> 4           NIPBL,MYC
#> 5               NIPBL
#> 6               NIPBL

4. Generate the visualization

visualizeRank(meanRank_results)

Session info

sessionInfo()
#> R version 4.5.0 (2025-04-11)
#> Platform: aarch64-apple-darwin20
#> Running under: macOS Sequoia 15.6.1
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib 
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
#> 
#> locale:
#> [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> time zone: America/Toronto
#> tzcode source: internal
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] rChEA3_0.2.0
#> 
#> loaded via a namespace (and not attached):
#>  [1] gtable_0.3.6       jsonlite_2.0.0     dplyr_1.1.4        compiler_4.5.0    
#>  [5] crayon_1.5.3       tidyselect_1.2.1   dichromat_2.0-0.1  jquerylib_0.1.4   
#>  [9] scales_1.4.0       yaml_2.3.10        fastmap_1.2.0      ggplot2_4.0.0     
#> [13] R6_2.6.1           labeling_0.4.3     generics_0.1.4     curl_7.0.0        
#> [17] knitr_1.50         tibble_3.3.0       lubridate_1.9.4    bslib_0.9.0       
#> [21] pillar_1.11.1      RColorBrewer_1.1-3 rlang_1.1.6        cachem_1.1.0      
#> [25] xfun_0.53          S7_0.2.0           sass_0.4.10        timechange_0.3.0  
#> [29] cli_3.6.5          withr_3.0.2        magrittr_2.0.4     digest_0.6.37     
#> [33] grid_4.5.0         rstudioapi_0.17.1  lifecycle_1.0.4    vctrs_0.6.5       
#> [37] evaluate_1.0.5     glue_1.8.0         farver_2.1.2       rmarkdown_2.30    
#> [41] httr_1.4.7         tools_4.5.0        pkgconfig_2.0.3    htmltools_0.5.8.1

Citation

If you use this package, please cite:

Keenan, A.B., Torre, D., Lachmann, A., Leong, A.K., Wojciechowicz, M.L., Utti, V., Jagodnik, K.M., Kropiwnicki, E., Wang, Z., & Ma’ayan, A. (2019). ChEA3: transcription factor enrichment analysis by orthogonal omics integration. Nucleic Acids Research, 47(W1), W212–W224. doi:10.1093/nar/gkz446

Resources

ChEA3 Web Server - Interactive tool and detailed documentation
ChEA3 Publication - Original research article
rChEA3 GitHub - Package source code and issues

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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rChEA3: An R client for ChEA3 transcription factor enrichment API

Christophe Tav

October 2025