cTarget |
Definition for S3 class 'cTarget' |
dTarget |
Definition for S3 class 'dTarget' |
eGSEA |
Definition for S3 class 'eGSEA' |
eTarget |
Definition for S3 class 'eTarget' |
pNode |
Definition for S3 class 'pNode' |
pPerf |
Definition for S3 class 'pPerf' |
print.cTarget |
Definition for S3 class 'cTarget' |
print.dTarget |
Definition for S3 class 'dTarget' |
print.eGSEA |
Definition for S3 class 'eGSEA' |
print.eTarget |
Definition for S3 class 'eTarget' |
print.pNode |
Definition for S3 class 'pNode' |
print.pPerf |
Definition for S3 class 'pPerf' |
print.sGS |
Definition for S3 class 'sGS' |
print.sTarget |
Definition for S3 class 'sTarget' |
sGS |
Definition for S3 class 'sGS' |
sTarget |
Definition for S3 class 'sTarget' |
xContour |
Function to visualise a numeric matrix as a contour plot |
xCorrelation |
Function to calculate and visualise correlation |
xGSEAbarplot |
Function to visualise GSEA results using a barplot |
xGSEAconciser |
Function to make GSEA results conciser by removing redundant terms |
xGSEAdotplot |
Function to visualise GSEA results using dot plot |
xGSsimulator |
Function to simulate gold standard negatives (GSN) given gold standard positives (GSP) and a gene network |
xMLcaret |
Function to integrate predictor matrix in a supervised manner via machine learning algorithms using caret. |
xMLcompare |
Function to visualise cross-validation performance against tuning parameters |
xMLdensity |
Function to visualise machine learning results using density plot |
xMLdotplot |
Function to visualise machine learning results using dot plot |
xMLfeatureplot |
Function to visualise/assess features used for machine learning |
xMLglmnet |
Function to integrate predictor matrix in a supervised manner via machine learning algorithm glmnet. |
xMLparameters |
Function to visualise cross-validation performance against tuning parameters |
xMLrandomforest |
Function to integrate predictor matrix in a supervised manner via machine learning algorithm random forest. |
xMLrename |
Function to rename predictors used in machine learning |
xMLzoom |
Function to visualise machine learning results using zoom plot |
xPier |
Function to do prioritisation through random walk techniques |
xPierABF |
Function to prioritise genes based on seed eGenes identified through ABF integrating GWAS and eQTL summary data |
xPierABFheatmap |
Function to visualise ABF evidence using heatmap |
xPierAnno |
Function to prioritise seed genes only from a list of pNode objects using annotation data |
xPierCor |
Function to calculate correlation between prioritised genes and user-defined external data |
xPierCross |
Function to extract priority matrix from a list of dTarget/sTarget objects |
xPierEvidence |
Function to extract evidence from a list of pNode objects |
xPierGenes |
Function to prioritise genes from an input network and the weight info imposed on its nodes |
xPierGRs |
Function to prioritise genes given a list of genomic regions |
xPierGSEA |
Function to prioritise pathways based on GSEA analysis of prioritised genes |
xPierKEGG |
Function to visualise prioritised genes in terms of a KEGG pathway |
xPierManhattan |
Function to visualise prioritised genes using manhattan plot |
xPierMatrix |
Function to extract priority or evidence matrix from a list of pNode objects |
xPierPathways |
Function to prioritise pathways based on enrichment analysis of top prioritised genes |
xPierROCR |
Function to assess the dTarget performance via ROC and Precision-Recall (PR) analysis |
xPierSNPs |
Function to prioritise genes given a list of seed SNPs together with the significance level (e.g. GWAS reported p-values) |
xPierSNPsAdv |
Function to prepare genetic predictors given a list of seed SNPs together with the significance level (e.g. GWAS reported p-values) |
xPierSNPsAdvABF |
Function to prepare genetic predictors given GWAS summary data with eGenes identified through ABF |
xPierSNPsConsensus |
Function to resolve relative importance of distance weight and eQTL weight priorising consensus gene ranks given a list of seed SNPs together with the significance level (e.g. GWAS reported p-values) |
xPierSubnet |
Function to identify a gene network from top prioritised genes |
xPierTrack |
Function to visualise a prioritised gene using track plot |
xPierTrackAdv |
Function to visualise a list of prioritised genes using advanced track plot |
xPredictCompare |
Function to compare prediction performance results |
xPredictROCR |
Function to assess the prediction performance via ROC and Precision-Recall (PR) analysis |
xRWR |
Function to implement Random Walk with Restart (RWR) on the input graph |
xVisEvidence |
Function to visualise evidence for prioritised genes in a gene network |
xVisEvidenceAdv |
Function to visualise evidence and priority scores for prioritised genes in a gene network |