This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18266 genes and 3 clinical features across 102 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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1 gene correlated to 'AGE'.
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ADAP2|55803
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20 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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SFRS2|6427 , ABHD11|83451 , C14ORF126|112487 , CEBPZ|10153 , ZNF596|169270 , ...
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49 genes correlated to 'NEOADJUVANT.THERAPY'.
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SLC16A2|6567 , FYCO1|79443 , PIK3R1|5295 , BEND6|221336 , PTN|5764 , ...
Complete statistical result table is provided in Supplement Table 1
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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AGE | Spearman correlation test | N=1 | older | N=1 | younger | N=0 |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=20 | yes | N=3 | no | N=17 |
NEOADJUVANT THERAPY | t test | N=49 | yes | N=35 | no | N=14 |
Table S1. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 61.34 (6.8) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
Table S2. Get Full Table List of one gene significantly correlated to 'AGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
ADAP2|55803 | 0.4835 | 2.636e-07 | 0.00481 |
Figure S1. Get High-res Image As an example, this figure shows the association of ADAP2|55803 to 'AGE'. P value = 2.64e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

20 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S3. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 5 | |
YES | 97 | |
Significant markers | N = 20 | |
Higher in YES | 3 | |
Higher in NO | 17 |
Table S4. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
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SFRS2|6427 | -8.86 | 2.5e-11 | 4.38e-07 | 0.8454 |
ABHD11|83451 | 9.49 | 1.204e-10 | 2.11e-06 | 0.8866 |
C14ORF126|112487 | -7.27 | 2.121e-10 | 3.71e-06 | 0.8062 |
CEBPZ|10153 | -7.27 | 3.222e-10 | 5.64e-06 | 0.8 |
ZNF596|169270 | -9.26 | 2.072e-08 | 0.000363 | 0.901 |
CLK4|57396 | -8.55 | 2.571e-08 | 0.00045 | 0.8742 |
CDC40|51362 | -6.93 | 3.386e-08 | 0.000592 | 0.7959 |
VN1R1|57191 | -7.2 | 5.162e-08 | 0.000903 | 0.8206 |
SFRS13A|10772 | -7.71 | 5.721e-08 | 0.001 | 0.8412 |
TMEM161B|153396 | -7.3 | 2.174e-07 | 0.0038 | 0.8371 |
Figure S2. Get High-res Image As an example, this figure shows the association of SFRS2|6427 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.5e-11 with T-test analysis.

Table S5. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'
NEOADJUVANT.THERAPY | Labels | N |
NO | 4 | |
YES | 98 | |
Significant markers | N = 49 | |
Higher in YES | 35 | |
Higher in NO | 14 |
Table S6. Get Full Table List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
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SLC16A2|6567 | 13.43 | 8.527e-24 | 1.45e-19 | 0.9107 |
FYCO1|79443 | 11.64 | 1.205e-19 | 2.04e-15 | 0.8852 |
PIK3R1|5295 | 12.02 | 1.295e-18 | 2.2e-14 | 0.875 |
BEND6|221336 | 10.34 | 5.722e-17 | 9.71e-13 | 0.8622 |
PTN|5764 | 16.04 | 1.068e-13 | 1.81e-09 | 0.9898 |
LTBP3|4054 | 8.54 | 2.211e-13 | 3.75e-09 | 0.8036 |
CLCNKB|1188 | 8.48 | 2.26e-13 | 3.84e-09 | 0.8129 |
RRP9|9136 | -8.83 | 2.051e-12 | 3.48e-08 | 0.8393 |
TIMELESS|8914 | -13.15 | 2.276e-12 | 3.86e-08 | 0.9694 |
TBX4|9496 | 8.93 | 3.44e-12 | 5.84e-08 | 0.8144 |
Figure S3. Get High-res Image As an example, this figure shows the association of SLC16A2|6567 to 'NEOADJUVANT.THERAPY'. P value = 8.53e-24 with T-test analysis.

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Expresson data file = PRAD.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = PRAD.clin.merged.picked.txt
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Number of patients = 102
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Number of genes = 18266
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Number of clinical features = 3
For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R
For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.