List of Trajectory Inference Methods (https://github.com/dynverse/dynmethods#list-of-included-methods) and Benchmarking package (https://dynverse.org/)
Functional Pseudotime analysis (https://broadinstitute.github.io/2019_scWorkshop/functional-pseudotime-analysis.html), originally from the Hemberg lab course material
Velocyto (https://www.nature.com/articles/s41586-018-0414-6)
Others
Below are the examples of trajectory inference tools on cancer, with very poor documentation - not enough to reproduce.
Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution (https://www.nature.com/articles/s41467-019-13441-6) –> TRACER
High Resolution Comparison of Cancer-Related Developmental Processes Using Trajectory Alignment (https://www.biorxiv.org/content/10.1101/469601v1.full) –> devMap
Identification of grade and origin specific cell populations in serous epithelial ovarian cancer by single cell RNA-seq (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118828) [GSE118828]
Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer (https://www.cell.com/cell/fulltext/S0092-8674(17)31270-9?cid=tw%26p) [GSE103322]
Heterogeneity of Human Breast Stem and Progenitor Cells as Revealed by Transcriptional Profiling (https://www.cell.com/stem-cell-reports/fulltext/S2213-6711(18)30107-3)
Longitudinal single-cell RNA sequencing of patient-derived primary cells reveals drug-induced infidelity in stem cell hierarchy (https://www.nature.com/articles/s41467-018-07261-3) [GSE117872]
Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma (https://www.nature.com/articles/s41422-019-0195-y)