CSHMM-TFContinuous-State Hidden Markov Models Transcription Factors(TF) (CSHMM-TF) is a method which integrates probabilistic modeling of single cell RNA-seq data with the ability to assign TFs to specific activation points in the model. TFs are assumed to influence the emission probabilities for cells assigned to later time points allowing us to identify not just the TFs controlling each path but also their order of activation.https://github.com/jessica1338/CSHMM-TF-for-time-series-scRNA-Seq.gitcshmm-tfbiotools:cshmm-tfCommand-line toolhttp://edamontology.org/topic_0749Transcription factors and regulatory siteshttp://edamontology.org/topic_0204Gene regulationhttp://edamontology.org/topic_3170RNA-Seqhttp://edamontology.org/topic_2269Statistics and probabilityhttp://edamontology.org/topic_3500ZoologyPythonhttp://edamontology.org/operation_0335Formattinghttp://edamontology.org/operation_3359Splittinghttp://edamontology.org/operation_2495Expression analysishttp://edamontology.org/operation_3891Essential dynamics10.1371/JOURNAL.PCBI.100764432069291PMC7048296Ziv Bar-Josephzivbj@cs.cmu.eduPerson