Statistical Web Applications

A range of applications have been developed to allow interactive exploration and analytics of large omics datasets. Any difficulties using an application? Let us know about them.

Single-cell analysis

CiteFuse

A suite of tools for pre-processing, clustering, differential RNA and ADT expression analysis, ligand-receptor interaction analysis of CITE-seq data.

Shiny Package Publication

scClassify

Single cell classification of cell-type hierarchies based on ensemble learning and sample size estimation.

Shiny Package Publication

spicyR

Analysis of immunofluorescence, mass cytometry imaging and other assays that can deeply phenotype individual cells and their spatial location.

Shiny Package

lisaClust

Identification and visualisation of tissue microenvironments and regions of tissue where spatial associations between cell-types is similar.

Shiny Package

SimBench

A benchmark study of simulation methods for single-cell RNA sequencing data.

Shiny Package Publication

COVID-19 Cell Interaction

Between-cell-type communication for prediction of COVID-19 disease severity.

Shiny Package Publication

Proteomics & Metabolomics

KinasePA

Enables analysis of kinase perturbation experiments.

Shiny Package Publication

ClueR

Use of prior knowledge to cluster time series proteomics data.

Shiny Package Publication

QPEP

A benchmarking scoreboard and visual analytics tools for methods which affect proteomics quantitation.

Shiny Publication

QCMAP

Mass Spectrometry QC (QCMAP)

Quality control for Mass Spectrometry.

Shiny Package Publication

Hierarchical approach to RUV normalisation (hRUV)

Normalisation for large-scale data.

Shiny Package Publication

Genomics & Transcriptomics

PACMEN

A tool for exploring the relationships between mutations and gene expression changes in protein interaction subnetworks for 19 tissues analysed by TCGA. R function to produce your own PACMEN input found here.

Shiny Publication

MelanomaExplorer

Enables customised classification, scatterplots of pairs of variables, network visualisations, and survival analysis for a variety of publicly available melanoma datasets.

Shiny Publication

Heliocidaris erythrogramma Time Series Viewer

Quick and easy time-series plots of gene expression of a particular sea urching gene expression dataset.

Shiny Publication

bcGST

bcGST: Bias-Corrected Gene Set Test

Gene set test method for boutique arrays.

Shiny Publication

arrayQuality

Quality control for Microarray Datasets.

Shiny

CPOP

Cross-Platform Omics Prediction (CPOP)

A statistical machine learning framework for wider implementation of precision medicine

Shiny Package Publication