Kidney Renal Papillary Cell Carcinoma: Correlations between copy number and mRNA expression
Maintained by John Zhang (Dana-Farber Cancer Institute)
Overview
Introduction

A TCGA sample is profiled to detect the copy number variations and expressions of genes. This pipeline attempts to correlate copy number and expression data of genes across samples to determine if the copy number variations also result in differential expressions. This report contains the calculated correlation coefficients based on measurements of genomic copy number (log2) values and intensity of the expressions of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNA the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.47075, -0.2572, -0.0865, 0.0538, 0.19315, 0.3214, 0.4517, 0.581, 0.7221, respectively.

Results
Correlation results

Number of genes and samples used for the calculation are shown in Table 1. Figure 1 shows the distribution of calculated correlation coefficients and quantile-quantile plot of the calculated correlation coefficients against a normal distribution. Table 2 shows the top 20 features ordered by the value of correlation coefficients.

Table 1. Counts of mRNA and number of samples in copy number and expression data sets and common to both

Category | Copy number | Expression | Common
--- | --- | --- | ---
Sample | 43 | 16 | 8
Genes | 29390 | 17815 | 15551

Figure 1. Summary figures. Left: histogram showing the distribution of the calculated correlations across samples for all Genes. Right: QQ plot of the calculated correlations across samples. The QQ plot is used to plot the quantiles of the calculated correlation coefficients against that derived from a normal distribution. Points deviating from the blue line indicate deviation from normality.

Table 2. Get Full Table Top 20 features (defined by the feature column) ranked by correlation coefficients

feature | r | p-value | q-value | chrom | start | end | geneid
--- | --- | --- | --- | --- | --- | --- | ---
C6orf162 | 0.9908 | 1.90988421922e-06 | 0.0216761689832592 | 6 | 88103446 | 88108196 | 57150
KIAA1586 | 0.9873 | 5.08605225713055e-06 | 0.0288619925422163 | 6 | 57019343 | 57027954 | 57691
IFNW1 | 0.9846 | 0.00228188174867383 | 0.121283164050005 | 9 | 21130631 | 21132144 | 3467
CCDC23 | 0.9835 | 1.09973555733056e-05 | 0.0368484678660656 | 1 | 43045320 | 43055510 | 374969
CTAGE5 | 0.9826 | 1.29868534120003e-05 | 0.0368484678660656 | 14 | 38804247 | 38890342 | 4253
SQSTM1 | 0.9803 | 1.88506140199607e-05 | 0.0368911343805544 | 5 | 179180503 | 179197684 | 8878
OTOS | 0.9793 | 2.19700645918142e-05 | 0.0368911343805544 | 2 | 240727119 | 240728746 | 150677
CDK6 | 0.9776 | 2.74532308095488e-05 | 0.0368911343805544 | 7 | 92072171 | 92301148 | 1021
FER1L3 | 0.9776 | 2.76697204075749e-05 | 0.0368911343805544 | 10 | 95056176 | 95232029 | 26509
YRDC | 0.9771 | 2.95960677991758e-05 | 0.0368911343805544 | 1 | 38041201 | 38046452 | 79693
ACADVL | 0.9763 | 3.25047269362777e-05 | 0.0368911343805544 | 17 | 7063877 | 7069309 | 37
ATR | 0.9741 | 4.26365814143459e-05 | 0.0382720559127756 | 3 | 143650769 | 143780341 | 545
STARD4 | 0.9734 | 4.62811089787518e-05 | 0.0382720559127756 | 5 | 110861921 | 110876056 | 134429
DDX24 | 0.9732 | 4.72100369552919e-05 | 0.0382720559127756 | 14 | 93587021 | 93617311 | 57062
MTBP | 0.9703 | 6.40410364467492e-05 | 0.0444302610445739 | 8 | 121526847 | 121605056 | 27085
DKFZp434B1231 | 0.97 | 6.60081604937357e-05 | 0.0444302610445739 | 1 | 199448393 | 199464697 | 91156
ZNF124 | 0.9699 | 6.65506495329815e-05 | 0.0444302610445739 | 1 | 245385826 | 245401941 | 7678
C1orf26 | 0.9673 | 8.51691528573895e-05 | 0.0537013631774488 | 1 | 183392914 | 183527443 | 54823
POMGNT1 | 0.9643 | 0.000110765950121383 | 0.0614619222538718 | 1 | 46426942 | 46436685 | 55624
PRKAA2 | 0.9637 | 0.0001164957521822 | 0.0614619222538718 | 1 | 56883608 | 56946709 | 5563

Methods & Data
Input

Gene level (TCGA Level III) expression data and copy number data of the corresponding loci derived by using the CNTools package of Bioconductor were used for the calculations. Pearson correlation coefficients were calculated for each pair of genes shared by the two data sets across all the samples that were common.

Correlation across sample

Pairwise correlations between the log2 copy numbers and expressions of each gene across samples were calculated using Pearson correlation.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

Meta

- Maintainer = John Zhang

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