This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18344 genes and 7 clinical features across 47 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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1 gene correlated to 'AGE'.
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CDC42BPA|8476
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16 genes correlated to 'GENDER'.
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RPS4Y1|6192 , ZFY|7544 , XIST|7503 , KDM5D|8284 , DDX3Y|8653 , ...
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163 genes correlated to 'HISTOLOGICAL.TYPE'.
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FPGT|8790 , ADPRHL2|54936 , MED8|112950 , ATG4C|84938 , PTP4A2|8073 , ...
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No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', 'RADIATIONS.RADIATION.REGIMENINDICATION', and 'NEOADJUVANT.THERAPY'.
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=1 | older | N=1 | younger | N=0 |
GENDER | t test | N=16 | male | N=13 | female | N=3 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=163 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 | ||||
NEOADJUVANT THERAPY | t test | N=0 |
Time to Death | Duration (Months) | 1.2-211.2 (median=31.8) |
censored | N = 23 | |
death | N = 24 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 43.98 (12) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
CDC42BPA|8476 | 0.6407 | 1.229e-06 | 0.0225 |
GENDER | Labels | N |
FEMALE | 25 | |
MALE | 22 | |
Significant markers | N = 16 | |
Higher in MALE | 13 | |
Higher in FEMALE | 3 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
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RPS4Y1|6192 | 30.92 | 8.237e-25 | 1.51e-20 | 1 |
ZFY|7544 | 37.26 | 1.634e-24 | 2.99e-20 | 1 |
XIST|7503 | -21.86 | 9.377e-24 | 1.72e-19 | 1 |
KDM5D|8284 | 46.31 | 1.118e-22 | 2.05e-18 | 1 |
DDX3Y|8653 | 39 | 1.249e-20 | 2.29e-16 | 1 |
PRKY|5616 | 17.52 | 1.55e-20 | 2.84e-16 | 1 |
USP9Y|8287 | 36.25 | 3.803e-18 | 6.97e-14 | 1 |
NLGN4Y|22829 | 18.19 | 3.656e-17 | 6.7e-13 | 1 |
TSIX|9383 | -12.69 | 1.777e-15 | 3.26e-11 | 1 |
TTTY15|64595 | 38.53 | 1.154e-12 | 2.12e-08 | 1 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 89.63 (11) |
Score | N | |
50 | 1 | |
70 | 1 | |
80 | 3 | |
90 | 14 | |
100 | 8 | |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
ASTROCYTOMA | 15 | |
OLIGOASTROCYTOMA | 14 | |
OLIGODENDROGLIOMA | 18 | |
Significant markers | N = 163 |
ANOVA_P | Q | |
---|---|---|
FPGT|8790 | 5.938e-12 | 1.09e-07 |
ADPRHL2|54936 | 1.402e-10 | 2.57e-06 |
MED8|112950 | 1.71e-10 | 3.14e-06 |
ATG4C|84938 | 1.072e-09 | 1.97e-05 |
PTP4A2|8073 | 1.238e-09 | 2.27e-05 |
MRPS15|64960 | 1.406e-09 | 2.58e-05 |
C20ORF30|29058 | 2.397e-09 | 4.4e-05 |
AK2|204 | 2.639e-09 | 4.84e-05 |
C2ORF29|55571 | 2.856e-09 | 5.24e-05 |
SDHAF1|644096 | 4.32e-09 | 7.92e-05 |
No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 33 | |
YES | 14 | |
Significant markers | N = 0 |
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Expresson data file = LGG.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = LGG.clin.merged.picked.txt
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Number of patients = 47
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Number of genes = 18344
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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.