This pipeline uses various statistical tests to identify miRs whose log2 expression levels correlated to selected clinical features.
Testing the association between 512 miRs and 12 clinical features across 84 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one miRs.

1 miR correlated to 'AGE'.

HSAMIR548B

1 miR correlated to 'PATHOLOGY.T.STAGE'.

HSAMIR39262

2 miRs correlated to 'GENDER'.

HSAMIR3662 , HSAMIR1275

1 miR correlated to 'NUMBERPACKYEARSSMOKED'.

HSAMIR489

No miRs correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'HISTOLOGICAL.TYPE', 'COMPLETENESS.OF.RESECTION', 'NUMBER.OF.LYMPH.NODES', and 'RACE'.
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=1  older  N=1  younger  N=0 
NEOPLASM DISEASESTAGE  KruskalWallis test  N=0  
PATHOLOGY T STAGE  Spearman correlation test  N=1  higher stage  N=1  lower stage  N=0 
PATHOLOGY N STAGE  Wilcoxon test  N=0  
PATHOLOGY M STAGE  KruskalWallis test  N=0  
GENDER  Wilcoxon test  N=2  male  N=2  female  N=0 
HISTOLOGICAL TYPE  KruskalWallis test  N=0  
NUMBERPACKYEARSSMOKED  Spearman correlation test  N=1  higher numberpackyearssmoked  N=1  lower numberpackyearssmoked  N=0 
COMPLETENESS OF RESECTION  KruskalWallis test  N=0  
NUMBER OF LYMPH NODES  Spearman correlation test  N=0  
RACE  KruskalWallis test  N=0 
Time to Death  Duration (Years)  11991 (median=187.5) 
censored  N = 51  
death  N = 11  
Significant markers  N = 0 
AGE  Mean (SD)  65.48 (11) 
Significant markers  N = 1  
pos. correlated  1  
neg. correlated  0 
SpearmanCorr  corrP  Q  

HSAMIR548B  0.4403  0.0003416  0.175 
NEOPLASM.DISEASESTAGE  Labels  N 
STAGE IA  2  
STAGE IB  4  
STAGE IIA  13  
STAGE IIB  61  
STAGE III  2  
STAGE IV  2  
Significant markers  N = 0 
PATHOLOGY.T.STAGE  Mean (SD)  2.9 (0.43) 
N  
1  2  
2  6  
3  74  
4  2  
Significant markers  N = 1  
pos. correlated  1  
neg. correlated  0 
SpearmanCorr  corrP  Q  

HSAMIR39262  0.4642  0.0002752  0.141 
PATHOLOGY.N.STAGE  Labels  N 
class0  20  
class1  63  
Significant markers  N = 0 
PATHOLOGY.M.STAGE  Labels  N 
M0  39  
M1  2  
MX  43  
Significant markers  N = 0 
GENDER  Labels  N 
FEMALE  44  
MALE  40  
Significant markers  N = 2  
Higher in MALE  2  
Higher in FEMALE  0 
W(pos if higher in 'MALE')  wilcoxontestP  Q  AUC  

HSAMIR3662  7  9.973e05  0.0511  0.9588 
HSAMIR1275  67  0.0002019  0.103  0.8405 
HISTOLOGICAL.TYPE  Labels  N 
PANCREASADENOCARCINOMA DUCTAL TYPE  72  
PANCREASADENOCARCINOMAOTHER SUBTYPE  8  
PANCREASCOLLOID (MUCINOUS NONCYSTIC) CARCINOMA  3  
Significant markers  N = 0 
NUMBERPACKYEARSSMOKED  Mean (SD)  25.29 (15) 
Significant markers  N = 1  
pos. correlated  1  
neg. correlated  0 
SpearmanCorr  corrP  Q  

HSAMIR489  0.8277  7.568e05  0.0387 
COMPLETENESS.OF.RESECTION  Labels  N 
R0  52  
R1  25  
R2  1  
RX  2  
Significant markers  N = 0 
NUMBER.OF.LYMPH.NODES  Mean (SD)  2.73 (3) 
Significant markers  N = 0 

Expresson data file = PAADTP.miRseq_RPKM_log2.txt

Clinical data file = PAADTP.merged_data.txt

Number of patients = 84

Number of miRs = 512

Number of clinical features = 12
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.
In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.