TUTORIAL. SFPointer: A Systematic Identification of RBPs Driving Aberrant Splicing in Cancer

César Lobato, Marian Gimeno, Ángel Rubio and Juan A. Ferrer-Bonsoms

Tecnun (University of Navarra), Paseo Manuel Lardizábal 15, 20018 San Sebastián, SPAIN

This is the tutorial for the publication: "SFPointer: A Systematic Identification of RBPs Driving Aberrant Splicing in Cancer"

In this tutorial, we present the methodology to predict RBPs based on the splicing events predicted by EventPointer. For this we use a combination of CLIP experiments in POSTAR3 with transcriptomic data (See the main manuscript for more details).

Here, we show the pipeline using a experiment in which TDP43 specific splicing factor is knocked-down.

Library and source

library(parallel)
library(EventPointer)
load("./data/ResultsBootsTrapTDP43.RData")
load("./ExS_Postar3.RData")

EventPointer event detection

######1. detect all possible events in reference transcriptome ######
Eventsxisof_grch38 <- EventDetection_transcriptome(inputFile = "./Homo_sapiens.GRCh38.gtf",Transcriptome = "grch38",
                                                       Pathtxt = "./EP_events/",cores = 16)

#load("../Paper_SF_pointer_2_0/info_gencode24/EventsXtrans_gc24.RData")
######2. get psi of all the events ######


pathfiles <- dir("./GSE136366/kallisto_output/",full.names = TRUE)
RNA_seq <- getbootstrapdata(PathSamples = pathfiles,type = "kallisto")
save(RNA_seq,file="RNA_seq_GSE136366.RData")

PSI_evexp <- GetPSI_FromTranRef(Samples = RNA_seq,
                                PathsxTranscript = Eventsxisof_grch38,
                                Bootstrap = T,
                                Filter = T,
                                Qn = 0.001)

######3. run statistic (both the ST and ML version) ######
Cmatrix <- as.matrix(limma::makeContrasts(TDP43-KOTDP43, levels=c("TDP43", "KOTDP43")))


Dmatrix <- cbind(c(1,1,1,0,0,0),
                 c(0,0,0,1,1,1))

ResultsBootsTrapTDP43 <- EventPointer_Bootstraps(PSI = PSI_evexp$PSI,
                                                 Design = Dmatrix,
                                                 Contrast = Cmatrix,
                                                 cores = 6,
                                                 ram = 20,
                                                 nBootstraps = 1000,
                                                 UsePseudoAligBootstrap = 1,
                                                 Threshold = 0)

SFPrediction

######1. Fisher test ######
hyper_pred_TDP43 <- EventPointer:::SF_Prediction(ResultsBootsTrapTDP43$Pvalues, ExS_Postar3, method = "Fisher")
which(hyper_pred_TDP43[[1]][order(hyper_pred_TDP43[[1]]$Pvalue_hyp_PSI,decreasing = F),]$RBP == "TDP43" )
save(hyper_pred_TDP43,file = "hyper_pred_TDP43.RData")

######1. Poisson Binomial test ######
poisonBi_pred_TDP43 <- EventPointer:::SF_Prediction(ResultsBootsTrapTDP43$Pvalues, ExS_Postar3, method = "PoiBin")
which(poisonBi_pred_TDP43[[1]][order(poisonBi_pred_TDP43[[1]]$Pvalue_hyp_PSI,decreasing = F),]$RBP == "TDP43" )
save(poisonBi_pred_TDP43,file = "poisonBi_pred_TDP43.RData")

######1. Wilcoxon test ######
Wilcoxon_pred_TDP43 <- EventPointer:::SF_Prediction(ResultsBootsTrapTDP43$Pvalues, ExS_Postar3,method = "Wilcoxon")
which(Wilcoxon_pred_TDP43[[1]][order(Wilcoxon_pred_TDP43[[1]]$z.score,decreasing = F),]$RBP == "TDP43" )
save(Wilcoxon_pred_TDP43,file = "Wilcoxon_pred_TDP43.RData")

######1. GSEA test ######
Gsea_pred_TDP43 <- EventPointer:::SF_Prediction(ResultsBootsTrapTDP43$Pvalues, ExS_Postar3, method = "Gsea")
which(Gsea_pred_TDP43[[1]][order(Gsea_pred_TDP43[[1]]$pval,decreasing = F),]$pathway == "TDP43" )
save(Gsea_pred_TDP43,file = "Gsea_pred_TDP43.RData")
save(ResultsBootsTrapTDP43, file="ResultsBootsTrapTDP43.RData")