Ovarian Serous Cystadenocarcinoma: 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 0.00656, 0.0587, 0.11676, 0.19694, 0.2852, 0.373, 0.44306, 0.5089, 0.5796, 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 558 565 540
Genes 29390 18633 16124

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
TBP 0.8485 0 0 6 170705396 170723872 6908
KRAS 0.8126 0 0 12 25249447 25295121 3845
RANBP3 0.8027 0 0 19 5867150 5929113 8498
TYK2 0.7912 0 0 19 10322209 10352211 7297
KIAA1967 0.7867 0 0 8 22518202 22533929 57805
PSMF1 0.7827 0 0 20 1041939 1095971 9491
KLHL9 0.7781 0 0 9 21321020 21325371 55958
C8orf53 0.7762 0 0 8 117847923 117853380 84294
DERL1 0.7736 0 0 8 124094769 124123722 79139
PEX5 0.7728 0 0 12 7234225 7255343 5830
CHMP7 0.7719 0 0 8 23157114 23175452 91782
MTAP 0.7713 0 0 9 21792635 21855970 4507
ZNF623 0.7713 0 0 8 144802973 144809731 9831
WBP11 0.7689 0 0 12 14830679 14847668 51729
MTDH 0.7683 0 0 8 98725583 98807714 92140
RNF4 0.7671 0 0 4 2440605 2487382 6047
DCP1B 0.7661 0 0 12 1925475 1983938 196513
CUL4A 0.765 0 0 13 112911087 112967393 8451
NFYC 0.7605 0 0 1 40929953 41009860 4802
STK3 0.7589 0 0 8 99536043 99907085 6788
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.

Meta
  • Maintainer = John Zhang