This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.
Testing the association between 18198 genes and 7 clinical features across 39 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one genes.
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6 genes correlated to 'Time to Death'.
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ABLIM1|3983 , FAAH2|158584 , AURKA|6790 , C5ORF4|10826 , LMNB2|84823 , ...
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1 gene correlated to 'AGE'.
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SIX1|6495
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No genes correlated to 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', and 'GENDER'.
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=6 | shorter survival | N=3 | longer survival | N=3 |
AGE | Spearman correlation test | N=1 | older | N=1 | younger | N=0 |
NEOPLASM DISEASESTAGE | Kruskal-Wallis test | N=0 | ||||
PATHOLOGY T STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY N STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY M STAGE | Kruskal-Wallis test | N=0 | ||||
GENDER | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0.2-91.7 (median=13.3) |
censored | N = 10 | |
death | N = 29 | |
Significant markers | N = 6 | |
associated with shorter survival | 3 | |
associated with longer survival | 3 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
ABLIM1|3983 | 0.41 | 6.507e-07 | 0.012 | 0.215 |
FAAH2|158584 | 0.58 | 1.905e-06 | 0.035 | 0.226 |
AURKA|6790 | 2.8 | 5.307e-06 | 0.097 | 0.798 |
C5ORF4|10826 | 0.43 | 7.121e-06 | 0.13 | 0.25 |
LMNB2|84823 | 3.2 | 1.32e-05 | 0.24 | 0.764 |
MARCH4|57574 | 1.37 | 1.424e-05 | 0.26 | 0.729 |
AGE | Mean (SD) | 64.79 (8.4) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 3 | |
STAGE IA | 1 | |
STAGE IB | 1 | |
STAGE II | 11 | |
STAGE III | 19 | |
STAGE IV | 4 | |
Significant markers | N = 0 |
PATHOLOGY.T.STAGE | Mean (SD) | 2.26 (0.82) |
N | ||
1 | 7 | |
2 | 17 | |
3 | 13 | |
4 | 2 | |
Significant markers | N = 0 |
PATHOLOGY.N.STAGE | Mean (SD) | 0.44 (0.73) |
N | ||
0 | 25 | |
1 | 6 | |
2 | 5 | |
Significant markers | N = 0 |
PATHOLOGY.M.STAGE | Labels | N |
M0 | 31 | |
M1 | 2 | |
MX | 6 | |
Significant markers | N = 0 |
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Expresson data file = MESO-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = MESO-TP.merged_data.txt
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Number of patients = 39
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Number of genes = 18198
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Number of clinical features = 7
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 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 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 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.