This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 534 miRs and 5 clinical features across 482 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one miRs.

4 miRs correlated to 'Time to Death'.

HSAMIR222 , HSAMIR221 , HSAMIR148A , HSAMIR34A

3 miRs correlated to 'AGE'.

HSAMIR148A , HSAMIR210 , HSAMIR339

No miRs correlated to 'GENDER', 'KARNOFSKY.PERFORMANCE.SCORE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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=4  shorter survival  N=4  longer survival  N=0 
AGE  Spearman correlation test  N=3  older  N=3  younger  N=0 
GENDER  t test  N=0  
KARNOFSKY PERFORMANCE SCORE  Spearman correlation test  N=0  
RADIATIONS RADIATION REGIMENINDICATION  t test  N=0 
Time to Death  Duration (Months)  0.1127.6 (median=10.3) 
censored  N = 103  
death  N = 379  
Significant markers  N = 4  
associated with shorter survival  4  
associated with longer survival  0 
HazardRatio  Wald_P  Q  C_index  

HSAMIR222  1.27  6.105e09  3.3e06  0.563 
HSAMIR221  1.32  1.292e06  0.00069  0.554 
HSAMIR148A  1.21  2.856e05  0.015  0.564 
HSAMIR34A  1.2  7.211e05  0.038  0.54 
AGE  Mean (SD)  57.53 (15) 
Significant markers  N = 3  
pos. correlated  3  
neg. correlated  0 
SpearmanCorr  corrP  Q  

HSAMIR148A  0.2148  1.933e06  0.00103 
HSAMIR210  0.1952  1.587e05  0.00846 
HSAMIR339  0.1809  6.511e05  0.0346 
GENDER  Labels  N 
FEMALE  186  
MALE  296  
Significant markers  N = 0 
No miR related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE  Mean (SD)  77.61 (14) 
Significant markers  N = 0 

Expresson data file = GBMTP.mirna__h_mirna_8x15k__unc_edu__Level_3__unc_DWD_Batch_adjusted__data.data.txt

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

Number of patients = 482

Number of miRs = 534

Number of clinical features = 5
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 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.