(primary solid tumor cohort)
This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 17814 genes and 8 clinical features across 155 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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1 gene correlated to 'AGE'.
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ANAPC1
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21 genes correlated to 'GENDER'.
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DDX3Y , JARID1D , EIF1AY , RPS4Y1 , CYORF15A , ...
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153 genes correlated to 'HISTOLOGICAL.TYPE'.
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C20ORF24 , DYNLRB1 , AGR2 , C20ORF4 , C10ORF65 , ...
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1 gene correlated to 'PATHOLOGICSPREAD(M)'.
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KCNC2
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No genes correlated to 'Time to Death', 'PATHOLOGY.T', 'PATHOLOGY.N', and 'TUMOR.STAGE'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=1 | older | N=0 | younger | N=1 |
GENDER | t test | N=21 | male | N=13 | female | N=8 |
HISTOLOGICAL TYPE | t test | N=153 | colon mucinous adenocarcinoma | N=48 | colon adenocarcinoma | N=105 |
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=0 | ||||
PATHOLOGICSPREAD(M) | ANOVA test | N=1 | ||||
TUMOR STAGE | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 0.9-52 (median=5) |
censored | N = 64 | |
death | N = 11 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 70.55 (12) |
Significant markers | N = 1 | |
pos. correlated | 0 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
ANAPC1 | -0.385 | 7.58e-07 | 0.0135 |
GENDER | Labels | N |
FEMALE | 76 | |
MALE | 79 | |
Significant markers | N = 21 | |
Higher in MALE | 13 | |
Higher in FEMALE | 8 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
DDX3Y | 22.53 | 2.909e-50 | 5.18e-46 | 0.9742 |
JARID1D | 20.65 | 4.391e-46 | 7.82e-42 | 0.9787 |
EIF1AY | 20.41 | 2.042e-45 | 3.64e-41 | 0.9654 |
RPS4Y1 | 19.25 | 1.481e-42 | 2.64e-38 | 0.9509 |
CYORF15A | 18.57 | 1.055e-40 | 1.88e-36 | 0.9557 |
RPS4Y2 | 18.38 | 3.613e-40 | 6.43e-36 | 0.9625 |
UTY | 17.81 | 3.766e-38 | 6.71e-34 | 0.957 |
ZFY | 15.52 | 3.264e-33 | 5.81e-29 | 0.947 |
CYORF15B | 15.52 | 9.991e-33 | 1.78e-28 | 0.9452 |
USP9Y | 10.82 | 1.525e-20 | 2.72e-16 | 0.8946 |
HISTOLOGICAL.TYPE | Labels | N |
COLON ADENOCARCINOMA | 128 | |
COLON MUCINOUS ADENOCARCINOMA | 24 | |
Significant markers | N = 153 | |
Higher in COLON MUCINOUS ADENOCARCINOMA | 48 | |
Higher in COLON ADENOCARCINOMA | 105 |
T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') | ttestP | Q | AUC | |
---|---|---|---|---|
C20ORF24 | -8.52 | 1.126e-11 | 2.01e-07 | 0.8545 |
DYNLRB1 | -8.19 | 3.266e-11 | 5.82e-07 | 0.8376 |
AGR2 | 8.12 | 1.298e-10 | 2.31e-06 | 0.8721 |
C20ORF4 | -7.68 | 4.344e-10 | 7.74e-06 | 0.8398 |
C10ORF65 | -7.31 | 9.01e-10 | 1.6e-05 | 0.8115 |
PLA2G12B | -7.55 | 1.006e-09 | 1.79e-05 | 0.8301 |
RDHE2 | 7.41 | 1.669e-09 | 2.97e-05 | 0.8174 |
ASXL1 | -7.45 | 1.882e-09 | 3.35e-05 | 0.847 |
SLC5A6 | -7.37 | 2.279e-09 | 4.06e-05 | 0.8356 |
EIF6 | -7.39 | 2.672e-09 | 4.76e-05 | 0.8363 |
PATHOLOGY.T | Mean (SD) | 2.83 (0.6) |
N | ||
T1 | 4 | |
T2 | 31 | |
T3 | 105 | |
T4 | 13 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 0.59 (0.81) |
N | ||
N0 | 95 | |
N1 | 28 | |
N2 | 32 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 129 | |
M1 | 22 | |
M1A | 1 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
KCNC2 | 2.165e-14 | 3.86e-10 |
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Expresson data file = COAD-TP.medianexp.txt
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Clinical data file = COAD-TP.clin.merged.picked.txt
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Number of patients = 155
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Number of genes = 17814
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Number of clinical features = 8
For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels
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 multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' 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.