This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18210 genes and 5 clinical features across 152 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.
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1 gene correlated to 'Time to Death'.
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LRRC61|65999
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26 genes correlated to 'GENDER'.
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XIST|7503 , RPS4Y1|6192 , KDM5D|8284 , DDX3Y|8653 , USP9Y|8287 , ...
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No genes correlated to 'AGE', 'KARNOFSKY.PERFORMANCE.SCORE', 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=1 | shorter survival | N=1 | longer survival | N=0 |
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=26 | male | N=15 | female | N=11 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |
Time to Death | Duration (Months) | 0.2-54 (median=9.1) |
censored | N = 39 | |
death | N = 113 | |
Significant markers | N = 1 | |
associated with shorter survival | 1 | |
associated with longer survival | 0 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
LRRC61|65999 | 1.33 | 1.874e-07 | 0.0034 | 0.653 |
AGE | Mean (SD) | 59.74 (14) |
Significant markers | N = 0 |
GENDER | Labels | N |
FEMALE | 53 | |
MALE | 99 | |
Significant markers | N = 26 | |
Higher in MALE | 15 | |
Higher in FEMALE | 11 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
XIST|7503 | -39.42 | 1.453e-57 | 2.64e-53 | 1 |
RPS4Y1|6192 | 48.88 | 5.191e-54 | 9.45e-50 | 1 |
KDM5D|8284 | 47.52 | 7.562e-51 | 1.38e-46 | 1 |
DDX3Y|8653 | 51.73 | 7.177e-50 | 1.31e-45 | 1 |
USP9Y|8287 | 51.52 | 6.071e-48 | 1.1e-43 | 1 |
CYORF15A|246126 | 42.41 | 3.272e-44 | 5.95e-40 | 1 |
TSIX|9383 | -22.74 | 4.953e-42 | 9.01e-38 | 0.9977 |
EIF1AY|9086 | 41.86 | 1.563e-41 | 2.84e-37 | 1 |
ZFY|7544 | 50.2 | 3.146e-41 | 5.72e-37 | 1 |
PRKY|5616 | 25.86 | 3.571e-35 | 6.5e-31 | 0.9989 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 75.75 (14) |
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 = 5
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 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.