This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18174 genes and 7 clinical features across 75 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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16 genes correlated to 'GENDER'.
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XIST|7503 , RPS4Y1|6192 , KDM5C|8242 , ZFX|7543 , PRKY|5616 , ...
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2 genes correlated to 'DISTANT.METASTASIS'.
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CA8|767 , GLB1L2|89944
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66 genes correlated to 'LYMPH.NODE.METASTASIS'.
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CKMT1B|1159 , EPHA1|2041 , LRRC43|254050 , FAM116A|201627 , ACTG2|72 , ...
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43 genes correlated to 'NEOPLASM.DISEASESTAGE'.
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MAD2L1|4085 , CALHM1|255022 , UCK2|7371 , CLDN11|5010 , CDCA5|113130 , ...
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No genes correlated to 'Time to Death', and 'KARNOFSKY.PERFORMANCE.SCORE'.
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=16 | male | N=3 | female | N=13 |
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
DISTANT METASTASIS | ANOVA test | N=2 | ||||
LYMPH NODE METASTASIS | ANOVA test | N=66 | ||||
NEOPLASM DISEASESTAGE | ANOVA test | N=43 |
Time to Death | Duration (Months) | 0.5-182.7 (median=15.1) |
censored | N = 59 | |
death | N = 13 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 59.68 (13) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
MCCC2|64087 | 0.5368 | 1.166e-06 | 0.0212 |
GENDER | Labels | N |
FEMALE | 23 | |
MALE | 52 | |
Significant markers | N = 16 | |
Higher in MALE | 3 | |
Higher in FEMALE | 13 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
XIST|7503 | -13.36 | 2.403e-14 | 4.36e-10 | 0.982 |
RPS4Y1|6192 | 11.88 | 2.538e-11 | 4.61e-07 | 0.9562 |
KDM5C|8242 | -8.17 | 4.536e-10 | 8.24e-06 | 0.9356 |
ZFX|7543 | -6.99 | 9.264e-09 | 0.000168 | 0.8921 |
PRKY|5616 | 7.5 | 9.69e-09 | 0.000176 | 0.9164 |
KDM6A|7403 | -6.91 | 1.084e-08 | 0.000197 | 0.9105 |
TSIX|9383 | -7.64 | 1.31e-08 | 0.000238 | 0.9309 |
TXLNG|55787 | -6.28 | 5.748e-08 | 0.00104 | 0.8654 |
UBA1|7317 | -6.13 | 4.028e-07 | 0.00731 | 0.8796 |
ZNF275|10838 | -6.03 | 4.325e-07 | 0.00785 | 0.8671 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 86.67 (28) |
Score | N | |
0 | 1 | |
90 | 6 | |
100 | 5 | |
Significant markers | N = 0 |
DISTANT.METASTASIS | Labels | N |
M0 | 47 | |
M1 | 5 | |
MX | 17 | |
Significant markers | N = 2 |
ANOVA_P | Q | |
---|---|---|
CA8|767 | 4.604e-08 | 0.000837 |
GLB1L2|89944 | 1.735e-06 | 0.0315 |
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 15 | |
N1 | 12 | |
N2 | 3 | |
NX | 45 | |
Significant markers | N = 66 |
ANOVA_P | Q | |
---|---|---|
CKMT1B|1159 | 3.166e-10 | 5.75e-06 |
EPHA1|2041 | 1.705e-09 | 3.1e-05 |
LRRC43|254050 | 6.794e-09 | 0.000123 |
FAM116A|201627 | 1.243e-08 | 0.000226 |
ACTG2|72 | 5.468e-08 | 0.000994 |
FTSJD1|55783 | 5.497e-08 | 0.000999 |
CKMT1A|548596 | 6.101e-08 | 0.00111 |
SCAMP3|10067 | 7.084e-08 | 0.00129 |
SHMT2|6472 | 9.162e-08 | 0.00166 |
VPS53|55275 | 1.158e-07 | 0.0021 |
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 35 | |
STAGE II | 3 | |
STAGE III | 21 | |
STAGE IV | 8 | |
Significant markers | N = 43 |
ANOVA_P | Q | |
---|---|---|
MAD2L1|4085 | 4.473e-10 | 8.13e-06 |
CALHM1|255022 | 4.764e-10 | 8.66e-06 |
UCK2|7371 | 2.171e-08 | 0.000395 |
CLDN11|5010 | 6.151e-08 | 0.00112 |
CDCA5|113130 | 3.341e-07 | 0.00607 |
TCTA|6988 | 3.61e-07 | 0.00656 |
KIF4A|24137 | 3.678e-07 | 0.00668 |
CCL25|6370 | 3.766e-07 | 0.00684 |
EPR1|8475 | 3.968e-07 | 0.00721 |
CEP55|55165 | 4.624e-07 | 0.0084 |
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Expresson data file = KIRP-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = KIRP-TP.clin.merged.picked.txt
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Number of patients = 75
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Number of genes = 18174
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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.