Reproducible notebooks and analysis pipelines of manuscript titled "Alternative splicing programs in tumor development and progression".
Preprocessed input objects, raw outputs and supplementary data tables are available in the Zenodo collection
Figure 1- Figure 1: Pan cancer study overview
Figure 2- Figure 2: Impact of tumour purity on downstream RNA-seq analyses
- Figure S1: Calculating tumour purity with ESTIMATE
- Figure S2: Comparison of pan-cancer principal components with impurity
- Figure S3: Sample covariates on expression and splicing embeddings
Figure 3- Figure 3: Benchmarking TRex in simulation experiments
- Figure S4: Performance per method in the simulation benchmark
Figure 4- Figure 4: Pan-cancer view of AS events associated with tumour development and progression
- Figure S5: Summary of tumour-associated events
- Figure S6: Summary of stage associated events
- Figure S7: GORA of Hallmark gene sets across of DAS events
- Figure S8: Impurity associated changes of SE events from both models
- Figure S9: Clustering of tumour-associated changes per AS mechanism
- Figure S10: Clustering of stage-associated changes
- Figure S11: Clustering of impurity-associated changes in the tumour models
- Figure S12: Clustering of impurity-associated changes from the stage models
- Figure S13: Comparison of differential alternative splicing effects and differential gene expression changes
- Figure S14: Relationship between fraction of normal samples and significant events
- Figure S15: Comparison of TRex DAS effect sizes vs Khales2018 across cancers
Figure 5- Figure 5: KIRC case study of tumour associated AS programs
- Figure S15: KIRC case study
Supplementary tables- Table S1: R package versions
- Table S3: Tumour associated events
- Table S4: Stage-associated events
- Supplementary data table 1: Pan-cancer models
- Supplementary data table 2: Correlation of differential AS and differential expression