This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 19433 genes and 8 clinical features across 43 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

11 genes correlated to 'GENDER'.

XIST7503_CALCULATED , USP9Y8287_CALCULATED , TSIX9383_CALCULATED , ZFY7544_CALCULATED , PRKY5616_CALCULATED , ...

117 genes correlated to 'HISTOLOGICAL.TYPE'.

SEL1L6400_CALCULATED , BIRC5332_CALCULATED , EPR18475_CALCULATED , YAP110413_CALCULATED , BTBD690135_CALCULATED , ...

2 genes correlated to 'PATHOLOGY.N'.

NKX224821_CALCULATED , PEX5L51555_CALCULATED

1 gene correlated to 'PATHOLOGICSPREAD(M)'.

DBR151163_CALCULATED

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  

Time to Death  Cox regression test  N=0  
AGE  Spearman correlation test  N=0  
GENDER  t test  N=11  male  N=9  female  N=2 
HISTOLOGICAL TYPE  ANOVA test  N=117  
PATHOLOGY T  Spearman correlation test  N=0  
PATHOLOGY N  Spearman correlation test  N=2  higher pN  N=1  lower pN  N=1 
PATHOLOGICSPREAD(M)  ANOVA test  N=1  
TUMOR STAGE  Spearman correlation test  N=0 
Time to Death  Duration (Months)  154 (median=14) 
censored  N = 13  
death  N = 5  
Significant markers  N = 0 
AGE  Mean (SD)  70.37 (10) 
Significant markers  N = 0 
GENDER  Labels  N 
FEMALE  20  
MALE  23  
Significant markers  N = 11  
Higher in MALE  9  
Higher in FEMALE  2 
T(pos if higher in 'MALE')  ttestP  Q  AUC  

XIST7503_CALCULATED  19.68  5.119e22  9.94e18  1 
USP9Y8287_CALCULATED  28.46  3.31e21  6.43e17  1 
TSIX9383_CALCULATED  18.32  5.512e21  1.07e16  1 
ZFY7544_CALCULATED  22.33  4.944e20  9.6e16  1 
PRKY5616_CALCULATED  17.07  3.058e17  5.94e13  1 
RPS4Y16192_CALCULATED  19.5  1.478e15  2.87e11  1 
TMSB4Y9087_CALCULATED  17.9  3.703e15  7.19e11  1 
EIF1AY9086_CALCULATED  20.73  1.294e14  2.51e10  1 
KDM5D8284_CALCULATED  23.59  1.51e12  2.93e08  1 
UTY7404_CALCULATED  19.54  1.591e12  3.09e08  1 
HISTOLOGICAL.TYPE  Labels  N 
STOMACH ADENOCARCINOMA  DIFFUSE TYPE  2  
STOMACH ADENOCARCINOMA  NOT OTHERWISE SPECIFIED (NOS)  25  
STOMACH INTESTINAL ADENOCARCINOMA  MUCINOUS TYPE  1  
STOMACH INTESTINAL ADENOCARCINOMA  TUBULAR TYPE  1  
STOMACH INTESTINAL ADENOCARCINOMA  TYPE NOT OTHERWISE SPECIFIED (NOS)  9  
Significant markers  N = 117 
ANOVA_P  Q  

SEL1L6400_CALCULATED  7.396e13  1.44e08 
BIRC5332_CALCULATED  1.14e11  2.22e07 
EPR18475_CALCULATED  3.636e11  7.07e07 
YAP110413_CALCULATED  4.648e11  9.03e07 
BTBD690135_CALCULATED  1.764e10  3.43e06 
DLGAP59787_CALCULATED  4.193e10  8.15e06 
TK17083_CALCULATED  6.594e10  1.28e05 
REST5978_CALCULATED  8.98e10  1.74e05 
GRIK12897_CALCULATED  1.099e09  2.13e05 
SPC2557405_CALCULATED  1.494e09  2.9e05 
PATHOLOGY.T  Mean (SD)  2.74 (0.93) 
N  
T1  2  
T2  14  
T3  9  
T4  9  
Significant markers  N = 0 
PATHOLOGY.N  Mean (SD)  1.22 (1) 
N  
N0  8  
N1  14  
N2  5  
N3  5  
Significant markers  N = 2  
pos. correlated  1  
neg. correlated  1 
SpearmanCorr  corrP  Q  

NKX224821_CALCULATED  0.8641  2.19e07  0.00426 
PEX5L51555_CALCULATED  0.7489  1.933e06  0.0376 
PATHOLOGICSPREAD(M)  Labels  N 
M0  34  
M1  7  
MX  2  
Significant markers  N = 1 
ANOVA_P  Q  

DBR151163_CALCULATED  4.046e07  0.00786 

Expresson data file = STADTP.mRNAseq_RPKM_log2.txt

Clinical data file = STADTP.clin.merged.picked.txt

Number of patients = 43

Number of genes = 19433

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. KaplanMeier 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 twotailed P values were estimated using 'cor.test' function in R
For twoclass clinical features, twotailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2expression levels between the two clinical classes using 't.test' function in R
For multiclass clinical features (ordinal or nominal), oneway analysis of variance (Howell 2002) was applied to compare the log2expression 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.