(primary solid tumor cohort)
This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 17814 genes and 7 clinical features across 27 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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13 genes correlated to 'GENDER'.
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DDX3Y , RPS4Y1 , RPS4Y2 , EIF1AY , UTY , ...
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1 gene correlated to 'HISTOLOGICAL.TYPE'.
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PCDHA5
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No genes correlated to 'Time to Death', 'AGE', 'KARNOFSKY.PERFORMANCE.SCORE', 'HISTOLOGICCLASSIFICATION', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=13 | male | N=13 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=1 | ||||
HISTOLOGICCLASSIFICATION | t test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |
Time to Death | Duration (Months) | 0.1-134.3 (median=46.6) |
censored | N = 18 | |
death | N = 9 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 39.33 (9.1) |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 9 | |
MALE | 18 | |
Significant markers | N = 13 | |
Higher in MALE | 13 | |
Higher in FEMALE | 0 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
DDX3Y | 27.22 | 2.571e-19 | 4.58e-15 | 1 |
RPS4Y1 | 26.27 | 7.639e-19 | 1.36e-14 | 1 |
RPS4Y2 | 22.72 | 7.422e-18 | 1.32e-13 | 1 |
EIF1AY | 21.11 | 3.274e-15 | 5.83e-11 | 1 |
UTY | 15.83 | 4.102e-14 | 7.31e-10 | 1 |
TTTY14 | 14.98 | 9.764e-14 | 1.74e-09 | 1 |
CYORF15B | 11.67 | 1.584e-11 | 2.82e-07 | 0.9815 |
JARID1D | 13.62 | 3.137e-11 | 5.59e-07 | 1 |
ZFY | 11.65 | 6.005e-11 | 1.07e-06 | 0.9753 |
NLGN4Y | 9.19 | 1.73e-08 | 0.000308 | 0.9691 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 88.82 (12) |
Score | N | |
50 | 1 | |
80 | 3 | |
90 | 8 | |
100 | 5 | |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 10 | |
OLIGOASTROCYTOMA | 9 | |
OLIGODENDROGLIOMA | 8 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
PCDHA5 | 8.339e-09 | 0.000149 |
HISTOLOGICCLASSIFICATION | Labels | N |
GRADE II | 7 | |
GRADE III | 20 | |
Significant markers | N = 0 |
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Expresson data file = LGG-TP.medianexp.txt
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Clinical data file = LGG-TP.clin.merged.picked.txt
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Number of patients = 27
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Number of genes = 17814
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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 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.