This pipeline uses various statistical tests to identify mRNAs whose log2 expression levels correlated to selected clinical features.
Testing the association between 18210 genes and 7 clinical features across 152 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one genes.
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4 genes correlated to 'AGE'.
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LOC84856|84856 , CBARA1|10367 , NOL3|8996 , SSH3|54961
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5 genes correlated to 'GENDER'.
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CYORF15A|246126 , HDHD1A|8226 , NCRNA00183|554203 , CYORF15B|84663 , FRG1B|284802
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7 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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ZNF677|342926 , LOC80054|80054 , SP3|6670 , IPO7|10527 , TIAF1|9220 , ...
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No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', 'RACE', and 'ETHNICITY'.
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=4 | older | N=2 | younger | N=2 |
GENDER | Wilcoxon test | N=5 | male | N=5 | female | N=0 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | Wilcoxon test | N=7 | yes | N=7 | no | N=0 |
RACE | Kruskal-Wallis test | N=0 | ||||
ETHNICITY | Wilcoxon test | N=0 |
Time to Death | Duration (Months) | 0.2-54 (median=9.1) |
censored | N = 35 | |
death | N = 117 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 59.74 (14) |
Significant markers | N = 4 | |
pos. correlated | 2 | |
neg. correlated | 2 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
LOC84856|84856 | -0.3698 | 3.461e-06 | 0.063 |
CBARA1|10367 | -0.3613 | 4.793e-06 | 0.0873 |
NOL3|8996 | 0.3484 | 1.087e-05 | 0.198 |
SSH3|54961 | 0.3481 | 1.112e-05 | 0.202 |
GENDER | Labels | N |
FEMALE | 53 | |
MALE | 99 | |
Significant markers | N = 5 | |
Higher in MALE | 5 | |
Higher in FEMALE | 0 |
W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
CYORF15A|246126 | 3465 | 1.748e-18 | 3.18e-14 | 1 |
HDHD1A|8226 | 614 | 8.019e-15 | 1.46e-10 | 0.883 |
NCRNA00183|554203 | 625 | 1.121e-14 | 2.04e-10 | 0.8809 |
CYORF15B|84663 | 2376 | 3.492e-14 | 6.35e-10 | 1 |
FRG1B|284802 | 3743 | 1.516e-05 | 0.276 | 0.7134 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 75.75 (14) |
Significant markers | N = 0 |
7 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 102 | |
YES | 50 | |
Significant markers | N = 7 | |
Higher in YES | 7 | |
Higher in NO | 0 |
W(pos if higher in 'YES') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
ZNF677|342926 | 1332 | 1.801e-06 | 0.0328 | 0.7388 |
LOC80054|80054 | 3703 | 6.195e-06 | 0.113 | 0.7261 |
SP3|6670 | 1423 | 9.978e-06 | 0.182 | 0.721 |
IPO7|10527 | 1436 | 1.262e-05 | 0.23 | 0.7184 |
TIAF1|9220 | 3663 | 1.284e-05 | 0.234 | 0.7182 |
CEMP1|752014 | 3658 | 1.405e-05 | 0.256 | 0.7173 |
LPCAT4|254531 | 3652 | 1.563e-05 | 0.285 | 0.7161 |
RACE | Labels | N |
ASIAN | 5 | |
BLACK OR AFRICAN AMERICAN | 10 | |
WHITE | 136 | |
Significant markers | N = 0 |
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Expresson data file = GBM-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = GBM-TP.merged_data.txt
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Number of patients = 152
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Number of genes = 18210
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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.
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.