# Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene and Pathway Level

## Documentation for package ‘Pi’ version 1.14.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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
xPierMRS | Function to calculate multi-trait rating score from a list of dTarget/sTarget 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