This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18200 genes and 8 clinical features across 63 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.
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1 gene correlated to 'AGE'.
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MCCC2|64087
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13 genes correlated to 'GENDER'.
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XIST|7503 , RPS4Y1|6192 , KDM5C|8242 , UBA1|7317 , PRKY|5616 , ...
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21 genes correlated to 'PATHOLOGY.T'.
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UCK2|7371 , EIF3E|3646 , MAD2L1|4085 , ACBD6|84320 , PRCC|5546 , ...
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2 genes correlated to 'PATHOLOGICSPREAD(M)'.
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CA8|767 , RPIA|22934
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79 genes correlated to 'TUMOR.STAGE'.
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MAD2L1|4085 , UCK2|7371 , EIF3E|3646 , PRCC|5546 , PAICS|10606 , ...
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No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', and 'PATHOLOGY.N'.
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=1 | older | N=1 | younger | N=0 |
GENDER | t test | N=13 | male | N=3 | female | N=10 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=21 | higher pT | N=18 | lower pT | N=3 |
PATHOLOGY N | Spearman correlation test | N=0 | ||||
PATHOLOGICSPREAD(M) | ANOVA test | N=2 | ||||
TUMOR STAGE | Spearman correlation test | N=79 | higher stage | N=67 | lower stage | N=12 |
Time to Death | Duration (Months) | 0.5-123.6 (median=15.5) |
censored | N = 50 | |
death | N = 13 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 60.33 (13) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
MCCC2|64087 | 0.5619 | 1.65e-06 | 0.03 |
GENDER | Labels | N |
FEMALE | 20 | |
MALE | 43 | |
Significant markers | N = 13 | |
Higher in MALE | 3 | |
Higher in FEMALE | 10 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
XIST|7503 | -11.68 | 7.289e-12 | 1.33e-07 | 0.9792 |
RPS4Y1|6192 | 11.18 | 1.276e-10 | 2.32e-06 | 0.9549 |
KDM5C|8242 | -8.47 | 1.524e-10 | 2.77e-06 | 0.9465 |
UBA1|7317 | -6.63 | 5.222e-08 | 0.00095 | 0.8919 |
PRKY|5616 | 6.99 | 6.204e-08 | 0.00113 | 0.9151 |
KDM6A|7403 | -5.99 | 3.694e-07 | 0.00672 | 0.8965 |
TSIX|9383 | -6.71 | 4.703e-07 | 0.00855 | 0.9215 |
ZFX|7543 | -5.93 | 4.708e-07 | 0.00856 | 0.8721 |
IGSF9B|22997 | -5.67 | 5.808e-07 | 0.0106 | 0.8477 |
MAGEE1|57692 | -6.03 | 6.519e-07 | 0.0119 | 0.8663 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 83.75 (34) |
Score | N | |
0 | 1 | |
90 | 3 | |
100 | 4 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 1.86 (0.93) |
N | ||
T1 | 32 | |
T2 | 8 | |
T3 | 23 | |
Significant markers | N = 21 | |
pos. correlated | 18 | |
neg. correlated | 3 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
UCK2|7371 | 0.6685 | 2.14e-09 | 3.9e-05 |
EIF3E|3646 | 0.6206 | 5.78e-08 | 0.00105 |
MAD2L1|4085 | 0.6113 | 1.027e-07 | 0.00187 |
ACBD6|84320 | 0.6034 | 1.661e-07 | 0.00302 |
PRCC|5546 | 0.6 | 2.03e-07 | 0.00369 |
NUF2|83540 | 0.595 | 2.709e-07 | 0.00493 |
GPR19|2842 | 0.5953 | 4.2e-07 | 0.00764 |
PAICS|10606 | 0.5853 | 4.689e-07 | 0.00853 |
ENY2|56943 | 0.5844 | 4.946e-07 | 0.009 |
EPHA1|2041 | -0.5826 | 5.451e-07 | 0.00992 |
PATHOLOGY.N | Mean (SD) | 0.58 (0.7) |
N | ||
N0 | 14 | |
N1 | 9 | |
N2 | 3 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 42 | |
M1 | 5 | |
MX | 9 | |
Significant markers | N = 2 |
ANOVA_P | Q | |
---|---|---|
CA8|767 | 1.585e-08 | 0.000288 |
RPIA|22934 | 7.612e-07 | 0.0139 |
TUMOR.STAGE | Mean (SD) | 2.02 (1.2) |
N | ||
Stage 1 | 29 | |
Stage 2 | 3 | |
Stage 3 | 16 | |
Stage 4 | 7 | |
Significant markers | N = 79 | |
pos. correlated | 67 | |
neg. correlated | 12 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
MAD2L1|4085 | 0.7346 | 1.729e-10 | 3.15e-06 |
UCK2|7371 | 0.7256 | 3.678e-10 | 6.69e-06 |
EIF3E|3646 | 0.7126 | 1.045e-09 | 1.9e-05 |
PRCC|5546 | 0.7046 | 1.933e-09 | 3.52e-05 |
PAICS|10606 | 0.6664 | 2.803e-08 | 0.00051 |
EPR1|8475 | 0.6699 | 3.023e-08 | 0.00055 |
NUF2|83540 | 0.6584 | 4.667e-08 | 0.000849 |
PABPC1|26986 | 0.648 | 8.873e-08 | 0.00161 |
CENPF|1063 | 0.6467 | 9.627e-08 | 0.00175 |
KIF4A|24137 | 0.6395 | 1.48e-07 | 0.00269 |
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Expresson data file = KIRP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = KIRP.clin.merged.picked.txt
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Number of patients = 63
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Number of genes = 18200
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Number of clinical features = 8
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.