The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization
Abstract
Reactome is a manually curated pathway annotation database for unveiling high-order biological pathways from high-throughput data. ReactomePA is an R/Bioconductor package providing enrichment analyses, including hypergeometric test and gene set enrichment analyses. A functional analysis can be applied to the genomic coordination obtained from a sequencing experiment to analyze the functional significance of genomic loci including cis-regulatory elements and non-coding regions. Comparison among different experiments is also supported. Moreover, ReactomePA provides several visualization functions to produce highly customizable, publication-quality figures. The source code and documents of ReactomePA are freely available through Bioconductor (http://www.bioconductor.org/packages/ReactomePA).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
Self-citationMolecular mechanisms of epithelial–mesenchymal transition
Lamouille, S., Xu, J., & Derynck, R. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3758 · Cited by 8,091
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
The human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304
Widespread plasticity in CTCF occupancy linked to DNA methylation
Wang, H., Maurano, M. T., Qu, H., Varley, K. E., Gertz, J., Pauli, F., Lee, K., Canfield, T., Weaver, M., Sandstrom, R., et al. (2012) · Genome Research · doi:10.1101/gr.136101.111 · Cited by 588
Pemberton, H., Anderton, E., Patel, H., Brookes, S., Chandler, H., Palermo, R., Stock, J., Rodriguez-Niedenführ, M., Racek, T., de Breed, L., et al. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r23 · Cited by 50
Cited by
clusterProfiler 4.0: A universal enrichment tool for interpreting omics data
(2021) · doi:10.1016/j.xinn.2021.100141 · Cited by 12,455
A human liver cell atlas reveals heterogeneity and epithelial progenitors
Aizarani, N., Saviano, A., Sagar, Mailly, L., Durand, S., Herman, J. S., Pessaux, P., Baumert, T. F., & Grün, D. (2019) · Nature · doi:10.1038/s41586-019-1373-2 · Cited by 1,147
Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.037 · Cited by 1,046
Multi-omic machine learning predictor of breast cancer therapy response
Sammut, S.-J., Crispin-Ortuzar, M., Chin, S.-F., Provenzano, E., Bardwell, H. A., Ma, W., Cope, W., Dariush, A., Dawson, S.-J., Abraham, J. E., et al. (2022) · Nature · doi:10.1038/s41586-021-04278-5 · Cited by 654
Deep Visual Proteomics defines single-cell identity and heterogeneity
Mund, A., Coscia, F., Kriston, A., Hollandi, R., Kovács, F., Brunner, A.-D., Migh, E., Schweizer, L., Santos, A., Bzorek, M., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01302-5 · Cited by 562
Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy
Chaffin, M., Papangeli, I., Simonson, B., Akkad, A.-D., Hill, M. C., Arduini, A., Fleming, S. J., Melanson, M., Hayat, S., Kost-Alimova, M., et al. (2022) · Nature · doi:10.1038/s41586-022-04817-8 · Cited by 418
Exploring Epigenomic Datasets by ChIPseeker
Wang, Q., Li, M., Wu, T., Zhan, L., Li, L., Chen, M., Xie, W., Xie, Z., Hu, E., Xu, S., et al. (2022) · Current Protocols · doi:10.1002/cpz1.585 · Cited by 415
Self-citationTracking early lung cancer metastatic dissemination in TRACERx using ctDNA
Abbosh, C., Frankell, A. M., Harrison, T., Kisistok, J., Garnett, A., Johnson, L., Veeriah, S., Moreau, M., Chesh, A., Chaunzwa, T. L., et al. (2023) · Nature · doi:10.1038/s41586-023-05776-4 · Cited by 382
Cai, Y., Zhang, Y., Loh, Y. P., Tng, J. Q., Lim, M. C., Cao, Z., Raju, A., Lieberman Aiden, E., Li, S., Manikandan, L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-20940-y · Cited by 321
Müller, P. M., Rademacher, J., Bagshaw, R. D., Wortmann, C., Barth, C., van Unen, J., Alp, K. M., Giudice, G., Eccles, R. L., Heinrich, L. E., et al. (2020) · Nature Cell Biology · doi:10.1038/s41556-020-0488-x · Cited by 253
Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies
Reichart, D., Lindberg, E. L., Maatz, H., Miranda, A. M. A., Viveiros, A., Shvetsov, N., Gärtner, A., Nadelmann, E. R., Lee, M., Kanemaru, K., et al. (2022) · Science · doi:10.1126/science.abo1984 · Cited by 240
Tumor microbiome links cellular programs and immunity in pancreatic cancer
Ghaddar, B., Biswas, A., Harris, C., Omary, M. B., Carpizo, D. R., Blaser, M. J., & De, S. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.09.009 · Cited by 181
PHGDH defines a metabolic subtype in lung adenocarcinomas with poor prognosis
Zhang, B., Zheng, A., Hydbring, P., Ambroise, G., Ouchida, A. T., Goiny, M., Vakifahmetoglu-Norberg, H., & Norberg, E. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.05.067 · Cited by 178
Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages
Ng, C. K. Y., Dazert, E., Boldanova, T., Coto-Llerena, M., Nuciforo, S., Ercan, C., Suslov, A., Meier, M.-A., Bock, T., Schmidt, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29960-8 · Cited by 165
Chen, S., Chang, Y., Li, L., Acosta, D., Li, Y., Guo, Q., Wang, C., Turkes, E., Morrison, C., Julian, D., et al. (2022) · Acta Neuropathologica Communications · doi:10.1186/s40478-022-01494-6 · Cited by 144
Western, D., Timsina, J., Wang, L., Wang, C., Yang, C., Phillips, B., Wang, Y., Liu, M., Ali, M., Beric, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01972-8 · Cited by 111
Kirsher, D. Y., Chand, S., Phong, A., Nguyen, B., Szoke, B. G., & Ahadi, S. (2025) · Communications Chemistry · doi:10.1038/s42004-025-01665-1 · Cited by 111
Single-cell and bulk transcriptomics of the liver reveals potential targets of NASH with fibrosis
Wang, Z.-Y., Keogh, A., Waldt, A., Cuttat, R., Neri, M., Zhu, S., Schuierer, S., Ruchti, A., Crochemore, C., Knehr, J., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-98806-y · Cited by 103
The little skate genome and the evolutionary emergence of wing-like fins
Marlétaz, F., de la Calle-Mustienes, E., Acemel, R. D., Paliou, C., Naranjo, S., Martínez-García, P. M., Cases, I., Sleight, V. A., Hirschberger, C., Marcet-Houben, M., et al. (2023) · Nature · doi:10.1038/s41586-023-05868-1 · Cited by 71
The FAK inhibitor BI 853520 exerts anti-tumor effects in breast cancer
Tiede, S., Meyer-Schaller, N., Kalathur, R. K. R., Ivanek, R., Fagiani, E., Schmassmann, P., Stillhard, P., Häfliger, S., Kraut, N., Schweifer, N., et al. (2018) · Oncogenesis · doi:10.1038/s41389-018-0083-1 · Cited by 66
Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases
Yasumizu, Y., Takeuchi, D., Morimoto, R., Takeshima, Y., Okuno, T., Kinoshita, M., Morita, T., Kato, Y., Wang, M., Motooka, D., et al. (2024) · Cell Genomics · doi:10.1016/j.xgen.2023.100473 · Cited by 60
Nuclear receptor REVERBα is a state-dependent regulator of liver energy metabolism
Hunter, A. L., Pelekanou, C. E., Adamson, A., Downton, P., Barron, N. J., Cornfield, T., Poolman, T. M., Humphreys, N., Cunningham, P. S., Hodson, L., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2005330117 · Cited by 54
HNF4A modulates glucocorticoid action in the liver
Hunter, A. L., Poolman, T. M., Kim, D., Gonzalez, F. J., Bechtold, D. A., Loudon, A. S. I., Iqbal, M., & Ray, D. W. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110697 · Cited by 49
Reschke, C. R., Silva, L. F. A., Vangoor, V. R., Rosso, M., David, B., Cavanagh, B. L., Connolly, N. M. C., Brennan, G. P., Sanz-Rodriguez, A., Mooney, C., et al. (2021) · Molecular Therapy · doi:10.1016/j.ymthe.2021.02.021 · Cited by 42
Heimberg, G., Kuo, T., DePianto, D., Heigl, T., Diamant, N., Salem, O., Scalia, G., Biancalani, T., Turley, S., Rock, J., et al. (2023) · doi:10.1101/2023.07.18.549537 · Cited by 40
An integrated pan-cancer analysis of PSAT1: A potential biomarker for survival and immunotherapy
Feng, M., Cui, H., Tu, W., Li, L., Gao, Y., Chen, L., Li, D., Chen, X., Xu, F., Zhou, C., et al. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.975381 · Cited by 37
Brooks, L. R. K., & Mias, G. I. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00392 · Cited by 32
Proteogenomics reveals sex-biased aging genes and coordinated splicing in cardiac aging
Han, Y., Wennersten, S. A., Wright, J. M., Ludwig, R. W., Lau, E., & Lam, M. P. Y. (2022) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00244.2022 · Cited by 31
Inherited determinants of early recurrent somatic mutations in prostate cancer
Romanel, A., Garritano, S., Stringa, B., Blattner, M., Dalfovo, D., Chakravarty, D., Soong, D., Cotter, K. A., Petris, G., Dhingra, P., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00046-0 · Cited by 29
Minisini, M., Di Giorgio, E., Kerschbamer, E., Dalla, E., Faggiani, M., Franforte, E., Meyer-Almes, F.-J., Ragno, R., Antonini, L., Mai, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac081 · Cited by 28
Saponara, E., Penno, C., Orsini, V., Wang, Z.-Y., Fischer, A., Aebi, A., Matadamas-Guzman, M. L., Brun, V., Fischer, B., Brousseau, M., et al. (2023) · The American Journal of Pathology · doi:10.1016/j.ajpath.2022.10.008 · Cited by 22
Wiley, J. W., Higgins, G. A., & Hong, S. (2022) · PeerJ · doi:10.7717/peerj.13287 · Cited by 21
Impact of aging on meningeal gene expression
Neutzner, M., Kohler, C., Frank, S., Killer, H. E., & Neutzner, A. (2023) · Fluids and Barriers of the CNS · doi:10.1186/s12987-023-00412-9 · Cited by 17
CHAMP1 complex directs heterochromatin assembly and promotes homology-directed DNA repair
Li, F., Zhang, T., Syed, A., Elbakry, A., Holmer, N., Nguyen, H., Mukkavalli, S., Greenberg, R. A., & D’Andrea, A. D. (2025) · Nature Communications · doi:10.1038/s41467-025-56834-6 · Cited by 13
Morphologically intact airways in lung fibrosis have an abnormal proteome
Herrera, J. A., Dingle, L. A., Monetero, M. A., Venkateswaran, R. V., Blaikley, J. F., Granato, F., Pearson, S., Lawless, C., & Thornton, D. J. (2023) · Respiratory Research · doi:10.1186/s12931-023-02400-x · Cited by 12
Deuterium labeling enables proteome-wide turnover kinetics analysis in cell culture
Alamillo, L., Ng, D. C. M., Currie, J., Black, A., Pandi, B., Manda, V., Pavelka, J., Schaal, P., Travers, J. G., McKinsey, T. A., et al. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101104 · Cited by 6
A ratiometric catalog of protein isoform shifts in the cardiac fetal gene program
Han, Y., Binti, S., Wennersten, S. A., Pandi, B., Ng, D. C. M., Lau, E., & Lam, M. P. Y. (2025) · JCI Insight · doi:10.1172/jci.insight.184309 · Cited by 5
Delineation of signaling routes that underlie differences in macrophage phenotypic states
(2025) · doi:10.1093/narmme/ugaf013 · Cited by 5
Lin, S., & Jia, P. (2024) · GigaScience · doi:10.1093/gigascience/giae108 · Cited by 4
Mori, L. P., Corley, M. J., McAuley, A. T., Pang, A., Venables, T., Ndhlovu, L. C., Pipkin, M. E., & Valente, S. T. (2024) · Life Science Alliance · doi:10.26508/lsa.202402653 · Cited by 4
Heritable Tissue‐Specific Gene Expression Associates With Chronic Wound Microbial Species
Omeir, K., Ancira, J., Gabrilska, R., Tipton, C., Miller, C., Noe, A., Subasinghe, K., Rowe, M., Phillips, N., Wolcott, J., et al. (2025) · Wound Repair and Regeneration · doi:10.1111/wrr.70055 · Cited by 3
Meinel, M., Langreder, N., Schmitt, A., Technau-Hafsi, K., Hillig, C., Roenneberg, S., Bernklauová, A., Říčař, J., Kacerovská, D., Wobser, M., et al. (2025) · doi:10.1101/2025.10.18.25338021 · Cited by 2
Fariha, F. T. J., Fuad, M., Saha, C. S., Hossen, S., & Hossain, M. J. (2025) · Scientific Reports · doi:10.1038/s41598-025-13315-6 · Cited by 1
Metadata
- Authors
- Yu, G., & He, Q.-Y.
- Venue
- Molecular BioSystems
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-11-23
- Volume
- 12
- Issue
- 2
- Pages
- 477-479
- ISSN
- 1742-2051 (ISSN-L)
- 1742-206X
- OpenAlex
- W2172557341
- Cited by
- 1,918
- References
- 7
- FWCI
- 14.54
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
