Lung Squamous Cell Carcinoma: Correlations between copy number and mRNAseq expression
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
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 Rnaseq 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 RNAseq expression of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNAseq the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 1104.8, 1780, 2368.4, 2973.2, 3605, 4290, 4957, 5614, 6318.2, 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 mRNAseq and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 282 223 223
Genes 22749 19444 18539

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

Locus ID Gene Symbol Cytoband cor p-value q-value
8772 FADD 11q13.3 0.869 0 0
220064 ORAOV1 11q13.3 0.8645 0 0
8500 PPFIA1 11q13.3 0.8605 0 0
9070 ASH2L 8p11.23 0.8549 0 0
51193 ZNF639 3q26.33 0.8516 0 0
54904 WHSC1L1 8p11.23 0.8511 0 0
54165 DCUN1D1 3q26.33 0.8398 0 0
55588 MED29 19q13.2 0.8356 0 0
59343 SENP2 3q27.2 0.8333 0 0
55234 SMU1 9p21.1 0.8222 0 0
55171 TBCCD1 3q27.3 0.8211 0 0
27257 LSM1 8p11.23 0.8203 0 0
8087 FXR1 3q26.33 0.8196 0 0
55290 BRF2 8p11.23 0.8163 0 0
23259 DDHD2 8p11.23 0.8152 0 0
23355 VPS8 3q27.2 0.8134 0 0
9530 BAG4 8p11.23 0.8124 0 0
208 AKT2 19q13.2 0.8092 0 0
11212 PROSC 8p11.23 0.8078 0 0
55324 ABCF3 3q27.1 0.8077 0 0
Methods & Data
Input

Gene level (TCGA Level III) mRNAseq expression data and copy number data of corresponding gene derived by GISTIC pipelinePearson 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. Location of data archives could not be determined.

Meta
  • Maintainer = TCGA GDAC Team