(primary solid tumor cohort)
This pipeline uses various statistical tests to identify miRs whose expression levels correlated to selected clinical features.
Testing the association between 427 genes and 9 clinical features across 143 samples, statistically thresholded by Q value < 0.05, 1 clinical feature related to at least one genes.
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1 gene correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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HSA-MIR-514-2
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No genes correlated to 'Time to Death', 'AGE', 'GENDER', 'HISTOLOGICAL.TYPE', 'PATHOLOGY.T', 'PATHOLOGY.N', 'PATHOLOGICSPREAD(M)', and 'TUMOR.STAGE'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=0 | ||||
HISTOLOGICAL TYPE | t test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=0 | ||||
PATHOLOGICSPREAD(M) | ANOVA test | N=0 | ||||
TUMOR STAGE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=1 | yes | N=1 | no | N=0 |
Time to Death | Duration (Months) | 0.2-121.1 (median=7) |
censored | N = 96 | |
death | N = 10 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 65.39 (12) |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 66 | |
MALE | 77 | |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
RECTAL ADENOCARCINOMA | 127 | |
RECTAL MUCINOUS ADENOCARCINOMA | 10 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 2.76 (0.67) |
N | ||
T1 | 9 | |
T2 | 26 | |
T3 | 97 | |
T4 | 10 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 0.67 (0.79) |
N | ||
N0 | 74 | |
N1 | 38 | |
N2 | 28 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 107 | |
M1 | 18 | |
M1A | 2 | |
MX | 14 | |
Significant markers | N = 0 |
TUMOR.STAGE | Mean (SD) | 2.41 (0.98) |
N | ||
Stage 1 | 28 | |
Stage 2 | 44 | |
Stage 3 | 43 | |
Stage 4 | 20 | |
Significant markers | N = 0 |
One gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 6 | |
YES | 137 | |
Significant markers | N = 1 | |
Higher in YES | 1 | |
Higher in NO | 0 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
HSA-MIR-514-2 | 5.99 | 0.000117 | 0.0478 | 0.8902 |
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Expresson data file = READ-TP.miRseq_RPKM_log2.txt
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Clinical data file = READ-TP.clin.merged.picked.txt
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Number of patients = 143
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Number of genes = 427
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Number of clinical features = 9
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. Kaplan-Meier 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 two-tailed P values were estimated using 'cor.test' function in R
For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R
For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression 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.