Correlations between APOBEC_MutLoad_MinEstimate and mRNAseq expression
Stomach and Esophageal carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by Hailei Zhang (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlations between APOBEC_MutLoad_MinEstimate and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1KP81PN
Overview
Introduction

This pipeline attempts to calculate the pearson correlation between APOBEC_MutLoad_MinEstimate and mRnaseq data of each gene across samples to determine if the APOBEC_MutLoad_MinEstimate also result in differential expressions.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.1399, -0.0963, -0.0656, -0.0369, -0.0086, 0.0194, 0.0497, 0.08814, 0.14597, respectively.

Results
Correlation results

Number of 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 genes ordered by the value of correlation coefficients.

Table 1.  Counts of mRNAseq and number of samples in APOBEC_MutLoad_MinEstimate and expression data sets and common to both

Category APOBEC_MutLoad_MinEstimate Expression Common
Sample 578 599 554

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 genes ranked by correlation coefficients

geneID cor p-value q-value
TMEM79|84283 0.3911 0 0
SLC38A2|54407 0.366 0 0
KRT1|3848 0.3654 8.88178419700125e-16 4.2687221279126e-13
C1orf74|148304 0.3643 0 0
GJB2|2706 0.3616 0 0
CAPNS2|84290 0.3598 1.82076576038526e-14 4.01510981325427e-12
KIAA1609|57707 0.3505 0 0
PERP|64065 0.3459 0 0
LGALS7|3963 0.3453 8.88178419700125e-16 4.2687221279126e-13
KRT14|3861 0.3437 2.59792187762287e-14 5.39688440457522e-12
PLS3|5358 0.3437 0 0
KRT16|3868 0.3434 4.44089209850063e-16 2.52242671194836e-13
DSC1|1823 0.3418 4.93161067538495e-13 5.70605620366762e-11
IGFL1|374918 0.3407 6.79190037544686e-12 5.46383607885733e-10
FAT2|2196 0.3404 2.22044604925031e-16 1.80956698900643e-13
APOBEC3A|200315 0.3397 4.44089209850063e-16 2.52242671194836e-13
PTHLH|5744 0.3397 2.22044604925031e-16 1.80956698900643e-13
KRT75|9119 0.3394 6.00298610820005e-09 1.83556234277491e-07
IL20RB|53833 0.3393 2.22044604925031e-16 1.80956698900643e-13
LYPD3|27076 0.3385 2.22044604925031e-16 1.80956698900643e-13
Methods & Data
Input

Gene level (TCGA Level III) mRNAseq expression data and APOBEC_MutLoad_MinEstimate derived by Mutation_APOBEC pipeline were used to do this analysis. Pearson correlation coefficients were calculated for APOBEC_MutLoad_MinEstimate and each gene across all the samples that were common.

Correlation across sample

Pearson correlation with pairwise.complete.obs was used to do this analysis.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.