Your gene list must tab-delimited, with gene names in the first column Click Here to downlad an example gene list If no gene list is uploaded, the genes AR, ESR1, HES6 MELK and STAT3 will be used If you want to analyse a single-gene, see the Quick Analysis tab

User Guide

Download User Guide

Citation

If you use any of the images generated in a publication or presentation, please cite: Dunning et al (2017). Mining the human prostate cancer datasets: The camcApp Shiny app. EBiomedicine. http://dx.doi.org/10.1016/j.ebiom.2017.02.022
Please also cite the relevant publication for the dataset;

Cambridge and Stockholm

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study. Ross-Adams et al. (2015) doi:10.1016/j.ebiom.2015.07.017

MSKCC

Integrative genomic profiling of human prostate cancer. Taylor et al. (2010) doi:10.1016/j.ccr.2010.05.026

Michigan2005

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression. Varambally et al. (2005) doi:10.1016/j.ccr.2005.10.001

Michigan2012

The Mutational Landscape of Lethal Castrate Resistant Prostate Cancer. Grasso et al. (2012) doi:10.1038/nature11125

About this app.............


cruk.cam.ac.uk This app was developed by Cancer Research Uk Cambridge Institute Source code available on github; https://github.com/crukci-bioinformatics/camcAPP

Features

Gene Profile

Produces boxplots to visualise the distribution of the selected genes. For each dataset, you can choose which clinical variable to group the samples on When choosing Cambridge or Stockholm, you will have the option to display the expression in the five different subtypes identified by Ross-Adams et al (2015). These subtypes were shown to have significantly different outcomes If multiple microarray probes are found for the gene, the probe with the highest inter-quartile range (IQR) will be picked An ANOVA analysis will also be performed to assess whether there are different expression levels in the groups you have chosen The boxplot can be exported as a pdf or png image. An R script can be downloaded, allowing you to repeat the analysis or tweak as you wish

Survival Analysis

You can perform Recursive Partitioning on a selected gene in a dataset with survival information (Cambridge, Stockholm and MSKCC). This analysis will determine if there are sub-groups of samples with significantly different expression level If samples in the dataset can be allocated into different groups based on the expression of the gene, a Kaplan-Meir plot will be displayed. Otherwise, the median expression level of the gene will be used to assign samples to high and low expression groups

Gene Correlation

You can plot one gene against another in a specified dataset. Points on the plot are coloured according to sample group. The correlation is computed and displayed.

Heatmap

The uploaded gene list can be used to generate a heatmap from the chosen dataset. Control is given over the distance metric and clustering method. Samples can be partitioned into different groups based on the clustering, and the composition of each group can be interrogated

Copy Number

For datasets with Copy number information (Cambridge, Stockholm and MSKCC), the frequency of alterations in different clinical covariates is displayed. A heatmap can also be generated We are very grateful to Emilie Lalonde from University of Toronto for supplying the data for these plots

Images

Spinning Wait Icons by Andrew Davidson http://andrewdavidson.com/articles/spinning-wait-icons/

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The covariates you can plot will be different for the various datasets
The z-score transformation is recommended to put the expression values for each gene onto comparable scales

Gene List plotting options

You can choose whether to plot all genes in the gene list on the same plot
If No is selected above, a particular gene from the list can be displayed

Output options

For more information on the different plot styles see the documentation for the ggthemes package
PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Plots and R scripts will have the extension pdf (/png) and R respectively Export current profile(s).... Download R script.... If you are using a gene list as input for the boxplots and have de-selected the composite plot option each gene will be plotted on a separate page

Gene Profile


            

ANOVA analysis

Here we show the results of an ANOVA (analysis of variance) analysis to assess whether there are changes in expression level between the defined groups

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You can select which gene to display the results for

Output options

PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Export K-M plot.... Download R script....

Citation for recursive partitioning (RP)

[1] Torsten Hothorn, Kurt Hornik and Achim Zeileis (2006). Unbiased Recursive Partitioning: A Conditional Inference Framework. Journal of Computational and Graphical Statistics, 15(3), 651--674.

            A recursive partitioning (RP) analysis [1] is performed to determine if the samples can be split into groups based on the expression data from your chosen gene(s). An RP p-value < 0.05 indicates a significant split. The p-value from RP and cut-off corresponding to a split are shown in the table below
            If no cut-off can be found with RP, the samples will be divided according to median expression level in the plots below
            
A histogram of expression level will be shown with a line to indicate the median expression level or RP cut-off
The grouping of samples found by RP, or using median expression level, is used to construct a Kaplan-Meier plot
The Kaplan-Meier plot is a useful way of summarising survival data. There is one curve for each group. Each curve starts at 100% probability of survival. The probability of freedom from biochemical recurrence is shown on the y axis and the time (in years) is shown on the x axis. The curve drops each time there is an 'event'. A cross is shown on each curve where a 'censoring'' event takes place. This is where someone drops out of the study for a reason not related to the study, e.g. the study ends before an event has occurred. These subjects are no longer included in any calculations. The lower the survival curve the worse prognosis the patients in that group have.

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Output options

For more information on the different plot styles see the documentation for the ggthemes package
PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Export Correlation plot .... Download R script....

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Output options

PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Export heatmap... Download R script....
Construcing a heatmap from the gene list you uploaded in the Analysis Parameters tab. If you haven't uploaded a gene list, an example gene list of three genes will be used

            
Sample Clustering
Select the number of clusters, k, from the slider

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Frequency: Overall Frequency of alterations in Cambridge, Stockholm and MSKCC Frequency in Dataset Frequency of alterations in a given covariate of interest in the chosen dataset Heatmap: Heatmap using the dataset that is currently selected
For more information on the different plot styles see the documentation for the ggthemes package
PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Export plot....

            The Proportion of amplifications and deletions will be shown for your chosen gene(s).
            

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Boxplot options

The covariates you can plot will be different for the various datasets

Output options

For more information on the different plot styles see the documentation for the ggthemes package
PDF can be imported into Illustrator (or similar) for editing. PNG plots are suitable for presentation PDF dimensions are measured in inches, and PNG dimensions are measured in pixels
Export Current plot.... Download R script....