This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 354 genes and 3 clinical features across 188 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.

7 genes correlated to 'Time to Death'.

HSAMIR362 , HSAMIR532 , HSAMIR181B1 , HSAMIR502 , HSAMIR660 , ...

5 genes correlated to 'AGE'.

HSAMIR598 , HSAMIR766 , HSAMIR29B1 , HSAMIR20B , HSAMIR363

3 genes correlated to 'GENDER'.

HSAMIR107 , HSAMIR1226 , HSAMIR505
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=7  shorter survival  N=6  longer survival  N=1 
AGE  Spearman correlation test  N=5  older  N=4  younger  N=1 
GENDER  t test  N=3  male  N=3  female  N=0 
Time to Death  Duration (Months)  0.994.1 (median=12) 
censored  N = 62  
death  N = 100  
Significant markers  N = 7  
associated with shorter survival  6  
associated with longer survival  1 
HazardRatio  Wald_P  Q  C_index  

HSAMIR362  1.51  2.917e06  0.001  0.669 
HSAMIR532  1.48  9.616e06  0.0034  0.668 
HSAMIR181B1  0.77  8.478e05  0.03  0.378 
HSAMIR502  1.43  8.721e05  0.031  0.644 
HSAMIR660  1.43  9.931e05  0.035  0.643 
HSAMIR501  1.33  0.000109  0.038  0.641 
HSAMIR188  1.38  0.0001184  0.041  0.635 
AGE  Mean (SD)  54.89 (16) 
Significant markers  N = 5  
pos. correlated  4  
neg. correlated  1 
SpearmanCorr  corrP  Q  

HSAMIR598  0.3159  1.653e05  0.00585 
HSAMIR766  0.2945  4.1e05  0.0145 
HSAMIR29B1  0.2923  4.689e05  0.0165 
HSAMIR20B  0.2895  5.577e05  0.0196 
HSAMIR363  0.2772  0.0001175  0.0411 
GENDER  Labels  N 
FEMALE  87  
MALE  101  
Significant markers  N = 3  
Higher in MALE  3  
Higher in FEMALE  0 
T(pos if higher in 'MALE')  ttestP  Q  AUC  

HSAMIR107  4.15  5.109e05  0.0181  0.6711 
HSAMIR1226  4.03  8.43e05  0.0298  0.6651 
HSAMIR505  4.02  8.681e05  0.0306  0.6749 

Expresson data file = LAMLTB.miRseq_RPKM_log2.txt

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

Number of patients = 188

Number of genes = 354

Number of clinical features = 3
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.