This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 817 miRs and 6 clinical features across 562 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one miRs.

5 miRs correlated to 'AGE'.

HSAMIR30B* , HSAMIR30D* , HSAMIR30B , HUR_4 , HSAMIR30D

14 miRs correlated to 'PRIMARY.SITE.OF.DISEASE'.

EBVMIRBART65P , HSAMIR96* , HSAMIR614 , KSHVMIRK129* , HSAMIR26A2* , ...

6 miRs correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

HSAMIR125B1* , HSAMIR3385P , EBVMIRBART175P , HSAMIR589* , HSAMIR518D5P , ...

No miRs correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', and 'NEOADJUVANT.THERAPY'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature  Statistical test  Significant miRs  Associated with  Associated with  

Time to Death  Cox regression test  N=0  
AGE  Spearman correlation test  N=5  older  N=1  younger  N=4 
PRIMARY SITE OF DISEASE  ANOVA test  N=14  
KARNOFSKY PERFORMANCE SCORE  Spearman correlation test  N=0  
RADIATIONS RADIATION REGIMENINDICATION  t test  N=6  yes  N=6  no  N=0 
NEOADJUVANT THERAPY  t test  N=0 
Time to Death  Duration (Months)  0.3180.2 (median=28.2) 
censored  N = 265  
death  N = 292  
Significant markers  N = 0 
AGE  Mean (SD)  59.68 (12) 
Significant markers  N = 5  
pos. correlated  1  
neg. correlated  4 
SpearmanCorr  corrP  Q  

HSAMIR30B*  0.2227  1.28e07  0.000105 
HSAMIR30D*  0.2187  2.161e07  0.000176 
HSAMIR30B  0.2048  1.254e06  0.00102 
HUR_4  0.1972  3.101e06  0.00252 
HSAMIR30D  0.1902  6.917e06  0.00562 
PRIMARY.SITE.OF.DISEASE  Labels  N 
OMENTUM  2  
OVARY  558  
PERITONEUM (OVARY)  2  
Significant markers  N = 14 
ANOVA_P  Q  

EBVMIRBART65P  5.151e15  4.21e12 
HSAMIR96*  6.953e13  5.67e10 
HSAMIR614  2.311e12  1.88e09 
KSHVMIRK129*  2.283e11  1.86e08 
HSAMIR26A2*  1.475e10  1.2e07 
EBVMIRBART9  2.28e10  1.85e07 
HSAMIR600  6.428e10  5.21e07 
HSAMIR548C3P  6.817e10  5.52e07 
HSAMIR374A*  4.249e09  3.44e06 
HCMVMIRUL36*  1.328e08  1.07e05 
No miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE  Mean (SD)  75.64 (13) 
Score  N  
40  2  
60  20  
80  49  
100  7  
Significant markers  N = 0 
6 miRs related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION  Labels  N 
NO  3  
YES  559  
Significant markers  N = 6  
Higher in YES  6  
Higher in NO  0 
T(pos if higher in 'YES')  ttestP  Q  AUC  

HSAMIR125B1*  12.11  2.011e17  1.64e14  0.7895 
HSAMIR3385P  12.61  1.412e15  1.15e12  0.802 
EBVMIRBART175P  7.93  6.434e14  5.24e11  0.6887 
HSAMIR589*  13.1  1.673e12  1.36e09  0.7651 
HSAMIR518D5P  6.99  4.74e10  3.85e07  0.6786 
HSAMIR4865P  15.93  2.182e08  1.77e05  0.8253 

Expresson data file = PANCANCER.mirna__h_mirna_8x15kv2__unc_edu__Level_3__unc_DWD_Batch_adjusted__data.data.txt

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

Number of patients = 562

Number of miRs = 817

Number of clinical features = 6
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 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 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 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.