Head and Neck 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 1013.9, 1729, 2310, 2942, 3597, 4245, 4887.3, 5534.2, 6278, 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 288 263 260
Genes 22749 19223 18370

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
8500 PPFIA1 11q13.3 0.9265 0 0
220064 ORAOV1 11q13.3 0.9099 0 0
8772 FADD 11q13.3 0.9001 0 0
55915 LANCL2 7p11.2 0.8815 0 0
3508 IGHMBP2 11q13.3 0.863 0 0
2017 CTTN 11q13.3 0.8604 0 0
329 BIRC2 11q22.2 0.8331 0 0
9070 ASH2L 8p11.23 0.8318 0 0
219931 TPCN2 11q13.3 0.8263 0 0
219927 MRPL21 11q13.3 0.8244 0 0
23081 KDM4C 9p24.1 0.8171 0 0
55664 CDC37L1 9p24.1 0.8039 0 0
92105 INTS4 11q14.1 0.8011 0 0
10413 YAP1 11q22.1 0.7969 0 0
54904 WHSC1L1 8p11.23 0.7925 0 0
114908 TMEM123 11q22.2 0.7914 0 0
55199 FAM86C1 11q13.4 0.7905 0 0
55191 NADSYN1 11q13.4 0.7894 0 0
11212 PROSC 8p11.23 0.7883 0 0
53407 STX18 4p16.3 0.7869 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