Identify at least 2, ideally 3 alternative methods that can use prior information (known targets of transcription factors) to predict TF activities on single-cell transcriptomic profiles.
These methods need to be free to use so that we can run them on simulated and real datasets.
Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data. https://doi.org/10.1093/nar/gkq149
Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data. https://doi.org/10.1093/nar/gkq149
PROGENy: Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, et al. Perturbation-response genes reveal signaling footprints in cancer gene expression [Internet]. Nature Communications. 2018; Available from: https://doi.org/10.1038/s41467-017-02391-6.
DoRothEA: Garcia-Alonso L, Holland CH, Ibrahim MM, Turei D, Saez-Rodriguez J. Benchmark and integration of resources for the estimation of human transcription factor activities. Genome Res. 2019;29:1363–75 Available from: https://doi.org/10.1101/gr.240663.118.
GO Enrichment: Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Michael Cherry J, et al. Gene Ontology: tool for the unification of biology. Nat Genet. 2000:25–9 Available from: https://doi.org/10.1038/75556.
SCENIC: Aibar S, González-Blas CB, Moerman T, Huynh-Thu VA, Imrichova H, Hulselmans G, et al. SCENIC: single-cell regulatory network inference and clustering. Nat Methods. 2017;14:1083–6 Available from: https://doi.org/10.1038/nmeth.4463.
metaVIPER: Ding H, Douglass EF Jr, Sonabend AM, Mela A, Bose S, Gonzalez C, et al. Quantitative assessment of protein activity in orphan tissues and single cells using the metaVIPER algorithm. Nat Commun. 2018;9:1471 Available from: https://doi.org/10.1038/s41467-018-03843-3.
Identify at least 2, ideally 3 alternative methods that can use prior information (known targets of transcription factors) to predict TF activities on single-cell transcriptomic profiles.
These methods need to be free to use so that we can run them on simulated and real datasets.
Here is a good starting point: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-1949-z