This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 19446 genes and 8 clinical features across 57 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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12 genes correlated to 'GENDER'.
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XIST|7503_CALCULATED , TSIX|9383_CALCULATED , USP9Y|8287_CALCULATED , ZFY|7544_CALCULATED , PRKY|5616_CALCULATED , ...
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207 genes correlated to 'HISTOLOGICAL.TYPE'.
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SEL1L|6400_CALCULATED , BIRC5|332_CALCULATED , EPR1|8475_CALCULATED , YAP1|10413_CALCULATED , KIF14|9928_CALCULATED , ...
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1 gene correlated to 'PATHOLOGY.N'.
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NKX2-2|4821_CALCULATED
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1 gene correlated to 'PATHOLOGICSPREAD(M)'.
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DBR1|51163_CALCULATED
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No genes correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T', and 'TUMOR.STAGE'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=12 | male | N=10 | female | N=2 |
HISTOLOGICAL TYPE | ANOVA test | N=207 | ||||
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=1 | higher pN | N=1 | lower pN | N=0 |
PATHOLOGICSPREAD(M) | ANOVA test | N=1 | ||||
TUMOR STAGE | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 1-54 (median=14) |
censored | N = 13 | |
death | N = 5 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 69.47 (10) |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 27 | |
MALE | 30 | |
Significant markers | N = 12 | |
Higher in MALE | 10 | |
Higher in FEMALE | 2 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
XIST|7503_CALCULATED | -21.75 | 5.317e-28 | 1.03e-23 | 1 |
TSIX|9383_CALCULATED | -20.77 | 5.06e-27 | 9.84e-23 | 1 |
USP9Y|8287_CALCULATED | 28.41 | 4.699e-26 | 9.13e-22 | 1 |
ZFY|7544_CALCULATED | 24.68 | 3.408e-25 | 6.62e-21 | 1 |
PRKY|5616_CALCULATED | 19.71 | 4.129e-22 | 8.02e-18 | 1 |
RPS4Y1|6192_CALCULATED | 23.26 | 4.954e-21 | 9.63e-17 | 1 |
EIF1AY|9086_CALCULATED | 24.47 | 1.08e-19 | 2.1e-15 | 1 |
DDX3Y|8653_CALCULATED | 24.25 | 3.132e-18 | 6.09e-14 | 1 |
TMSB4Y|9087_CALCULATED | 16.66 | 7.117e-16 | 1.38e-11 | 1 |
KDM5D|8284_CALCULATED | 27.22 | 7.23e-16 | 1.4e-11 | 1 |
HISTOLOGICAL.TYPE | Labels | N |
STOMACH ADENOCARCINOMA - DIFFUSE TYPE | 2 | |
STOMACH ADENOCARCINOMA - NOT OTHERWISE SPECIFIED (NOS) | 39 | |
STOMACH INTESTINAL ADENOCARCINOMA - MUCINOUS TYPE | 1 | |
STOMACH INTESTINAL ADENOCARCINOMA - TUBULAR TYPE | 1 | |
STOMACH INTESTINAL ADENOCARCINOMA - TYPE NOT OTHERWISE SPECIFIED (NOS) | 9 | |
Significant markers | N = 207 |
ANOVA_P | Q | |
---|---|---|
SEL1L|6400_CALCULATED | 5.961e-16 | 1.16e-11 |
BIRC5|332_CALCULATED | 1.773e-13 | 3.45e-09 |
EPR1|8475_CALCULATED | 4.607e-13 | 8.96e-09 |
YAP1|10413_CALCULATED | 4.904e-13 | 9.54e-09 |
KIF14|9928_CALCULATED | 1.914e-12 | 3.72e-08 |
BTBD6|90135_CALCULATED | 3.829e-12 | 7.44e-08 |
DLGAP5|9787_CALCULATED | 5.341e-12 | 1.04e-07 |
GRIK1|2897_CALCULATED | 2.02e-11 | 3.93e-07 |
PKP3|11187_CALCULATED | 4.738e-11 | 9.21e-07 |
TK1|7083_CALCULATED | 5.664e-11 | 1.1e-06 |
PATHOLOGY.T | Mean (SD) | 2.77 (0.87) |
N | ||
T1 | 2 | |
T2 | 14 | |
T3 | 14 | |
T4 | 9 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 1.21 (0.92) |
N | ||
N0 | 8 | |
N1 | 20 | |
N2 | 6 | |
N3 | 5 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
NKX2-2|4821_CALCULATED | 0.8067 | 1.112e-06 | 0.0216 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 48 | |
M1 | 7 | |
MX | 2 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
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DBR1|51163_CALCULATED | 5.879e-07 | 0.0114 |
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Expresson data file = STAD.mRNAseq_RPKM_log2.txt
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Clinical data file = STAD.clin.merged.picked.txt
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Number of patients = 57
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Number of genes = 19446
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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.