This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18632 genes and 6 clinical features across 562 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.
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1 gene correlated to 'Time to Death'.
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ZFHX4
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193 genes correlated to 'AGE'.
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STS , GREB1 , DEPDC6 , GNPNAT1 , SLCO1A2 , ...
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2 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.
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SPINK8 , PTBP1
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1 gene correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
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WDR60
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30 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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FLJ22662 , WDR62 , GLIPR1L2 , ATHL1 , ST6GALNAC6 , ...
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1 gene correlated to 'COMPLETENESS.OF.RESECTION'.
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IL1RAPL2
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=193 | older | N=75 | younger | N=118 |
PRIMARY SITE OF DISEASE | ANOVA test | N=2 | ||||
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=1 | higher score | N=1 | lower score | N=0 |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=30 | yes | N=15 | no | N=15 |
COMPLETENESS OF RESECTION | ANOVA test | N=1 |
Time to Death | Duration (Months) | 0.3-180.2 (median=28.6) |
censored | N = 264 | |
death | N = 293 | |
Significant markers | N = 1 | |
associated with shorter survival | 1 | |
associated with longer survival | 0 |
HazardRatio | Wald_P | Q | C_index | |
---|---|---|---|---|
ZFHX4 | 1.63 | 2.256e-06 | 0.042 | 0.575 |
AGE | Mean (SD) | 59.72 (12) |
Significant markers | N = 193 | |
pos. correlated | 75 | |
neg. correlated | 118 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
STS | -0.307 | 1.713e-13 | 3.19e-09 |
GREB1 | -0.3024 | 4.058e-13 | 7.56e-09 |
DEPDC6 | -0.301 | 5.286e-13 | 9.85e-09 |
GNPNAT1 | -0.2963 | 1.261e-12 | 2.35e-08 |
SLCO1A2 | 0.2853 | 8.849e-12 | 1.65e-07 |
EIF4E3 | -0.2847 | 9.779e-12 | 1.82e-07 |
NPAL2 | -0.2761 | 4.258e-11 | 7.93e-07 |
BRCC3 | -0.275 | 5.105e-11 | 9.51e-07 |
NLK | 0.2749 | 5.176e-11 | 9.64e-07 |
APPL2 | 0.2747 | 5.406e-11 | 1.01e-06 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
OMENTUM | 2 | |
OVARY | 558 | |
PERITONEUM OVARY | 2 | |
Significant markers | N = 2 |
One gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 75.64 (13) |
Score | N | |
40 | 2 | |
60 | 20 | |
80 | 49 | |
100 | 7 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
WDR60 | 0.504 | 2.551e-06 | 0.0475 |
30 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 3 | |
YES | 559 | |
Significant markers | N = 30 | |
Higher in YES | 15 | |
Higher in NO | 15 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
FLJ22662 | -24.23 | 4.068e-41 | 7.58e-37 | 0.867 |
WDR62 | -13.77 | 2.368e-35 | 4.41e-31 | 0.7513 |
GLIPR1L2 | -16.48 | 6.348e-35 | 1.18e-30 | 0.7794 |
ATHL1 | 12.49 | 3.399e-31 | 6.33e-27 | 0.6535 |
ST6GALNAC6 | 17.15 | 2.815e-20 | 5.24e-16 | 0.799 |
SDK1 | -15 | 2.746e-15 | 5.12e-11 | 0.768 |
CYP4A11 | 8.73 | 5.398e-15 | 1.01e-10 | 0.6184 |
LOC388161 | 22.94 | 2.065e-13 | 3.85e-09 | 0.9207 |
TMC5 | 8.42 | 5.86e-12 | 1.09e-07 | 0.5897 |
C9ORF114 | -11.98 | 2.006e-11 | 3.74e-07 | 0.7358 |
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 14 | |
R1 | 27 | |
R2 | 1 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
IL1RAPL2 | 6.299e-07 | 0.0117 |
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Expresson data file = OV-TP.medianexp.txt
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Clinical data file = OV-TP.merged_data.txt
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Number of patients = 562
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Number of genes = 18632
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Number of clinical features = 6
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.