This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 17995 genes and 14 clinical features across 413 samples, statistically thresholded by Q value < 0.05, 13 clinical features related to at least one genes.
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127 genes correlated to 'AGE'.
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ZNF518B|85460 , HCG11|493812 , C12ORF52|84934 , ASB13|79754 , RANBP17|64901 , ...
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39 genes correlated to 'GENDER'.
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RPS4Y1|6192 , ZFY|7544 , DDX3Y|8653 , UTY|7404 , NLGN4Y|22829 , ...
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4458 genes correlated to 'HISTOLOGICAL.TYPE'.
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ITGA3|3675 , FN1|2335 , KCNN4|3783 , UNC5CL|222643 , TMPRSS4|56649 , ...
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26 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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C14ORF180|400258 , FLJ37543|285668 , TAS2R43|259289 , ADIPOQ|9370 , HPR|3250 , ...
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6 genes correlated to 'RADIATIONEXPOSURE'.
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CRNN|49860 , C13ORF30|144809 , CSNK1A1P|161635 , CYP2C9|1559 , CYORF15A|246126 , ...
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8 genes correlated to 'DISTANT.METASTASIS'.
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C4ORF6|10141 , RNF207|388591 , CYP21A2|1589 , HSPA6|3310 , TAF1D|79101 , ...
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639 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.
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ASAH2|56624 , FAM69C|125704 , COL11A1|1301 , FAM169A|26049 , CYP26A1|1592 , ...
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1295 genes correlated to 'LYMPH.NODE.METASTASIS'.
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CREB5|9586 , KCNN4|3783 , ICAM1|3383 , MLEC|9761 , FN1|2335 , ...
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1 gene correlated to 'COMPLETENESS.OF.RESECTION'.
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CATSPER2P1|440278
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673 genes correlated to 'NUMBER.OF.LYMPH.NODES'.
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CBFB|865 , PELI1|57162 , FAM60A|58516 , ZNF346|23567 , CREB5|9586 , ...
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263 genes correlated to 'NEOPLASM.DISEASESTAGE'.
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GSPT2|23708 , SEMA3G|56920 , FAM50B|26240 , GJA5|2702 , MOGS|7841 , ...
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1 gene correlated to 'MULTIFOCALITY'.
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TMTC1|83857
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7 genes correlated to 'TUMOR.SIZE'.
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CLDN2|9075 , ZC3H10|84872 , C3ORF32|51066 , PI16|221476 , FOXI2|399823 , ...
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No genes correlated to 'Time to Death'
Complete statistical result table is provided in Supplement Table 1
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=127 | older | N=55 | younger | N=72 |
GENDER | t test | N=39 | male | N=16 | female | N=23 |
HISTOLOGICAL TYPE | ANOVA test | N=4458 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=26 | yes | N=18 | no | N=8 |
RADIATIONEXPOSURE | t test | N=6 | yes | N=2 | no | N=4 |
DISTANT METASTASIS | ANOVA test | N=8 | ||||
EXTRATHYROIDAL EXTENSION | ANOVA test | N=639 | ||||
LYMPH NODE METASTASIS | ANOVA test | N=1295 | ||||
COMPLETENESS OF RESECTION | ANOVA test | N=1 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=673 | higher number.of.lymph.nodes | N=377 | lower number.of.lymph.nodes | N=296 |
NEOPLASM DISEASESTAGE | ANOVA test | N=263 | ||||
MULTIFOCALITY | t test | N=1 | unifocal | N=0 | multifocal | N=1 |
TUMOR SIZE | Spearman correlation test | N=7 | higher tumor.size | N=0 | lower tumor.size | N=7 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0-147.4 (median=9.3) |
censored | N = 398 | |
death | N = 10 | |
Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 46.6 (16) |
Significant markers | N = 127 | |
pos. correlated | 55 | |
neg. correlated | 72 |
Table S3. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
ZNF518B|85460 | -0.3422 | 8.722e-13 | 1.57e-08 |
HCG11|493812 | -0.3173 | 4.093e-11 | 7.36e-07 |
C12ORF52|84934 | 0.3169 | 4.337e-11 | 7.8e-07 |
ASB13|79754 | 0.3115 | 9.585e-11 | 1.72e-06 |
RANBP17|64901 | -0.3114 | 1.14e-10 | 2.05e-06 |
STL|7955 | -0.3084 | 1.502e-10 | 2.7e-06 |
IL20RA|53832 | 0.3084 | 1.665e-10 | 2.99e-06 |
MSL3L2|151507 | -0.3052 | 2.381e-10 | 4.28e-06 |
EPN3|55040 | 0.297 | 7.373e-10 | 1.33e-05 |
GPI|2821 | 0.2903 | 1.825e-09 | 3.28e-05 |
Figure S1. Get High-res Image As an example, this figure shows the association of ZNF518B|85460 to 'AGE'. P value = 8.72e-13 with Spearman correlation analysis. The straight line presents the best linear regression.

Table S4. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 307 | |
MALE | 106 | |
Significant markers | N = 39 | |
Higher in MALE | 16 | |
Higher in FEMALE | 23 |
Table S5. Get Full Table List of top 10 genes differentially expressed by 'GENDER'
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
RPS4Y1|6192 | 83.65 | 1.028e-170 | 1.85e-166 | 1 |
ZFY|7544 | 84 | 3.646e-166 | 6.56e-162 | 1 |
DDX3Y|8653 | 87.01 | 1.572e-157 | 2.83e-153 | 1 |
UTY|7404 | 83.08 | 2.656e-132 | 4.78e-128 | 1 |
NLGN4Y|22829 | 60.52 | 2.266e-131 | 4.08e-127 | 1 |
KDM5D|8284 | 78.03 | 8.45e-123 | 1.52e-118 | 1 |
PRKY|5616 | 37.47 | 3.752e-112 | 6.75e-108 | 0.9924 |
USP9Y|8287 | 66.01 | 4.011e-109 | 7.21e-105 | 0.9999 |
XIST|7503 | -42.46 | 5.508e-72 | 9.91e-68 | 0.9928 |
CYORF15A|246126 | 53.1 | 4.894e-58 | 8.8e-54 | 1 |
Figure S2. Get High-res Image As an example, this figure shows the association of RPS4Y1|6192 to 'GENDER'. P value = 1.03e-170 with T-test analysis.

Table S6. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
HISTOLOGICAL.TYPE | Labels | N |
OTHER SPECIFY | 7 | |
THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | 286 | |
THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | 86 | |
THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) | 34 | |
Significant markers | N = 4458 |
Table S7. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'
ANOVA_P | Q | |
---|---|---|
ITGA3|3675 | 2.257e-37 | 4.06e-33 |
FN1|2335 | 2.785e-37 | 5.01e-33 |
KCNN4|3783 | 7.66e-35 | 1.38e-30 |
UNC5CL|222643 | 9.357e-35 | 1.68e-30 |
TMPRSS4|56649 | 1.292e-34 | 2.32e-30 |
MUC1|4582 | 1.912e-34 | 3.44e-30 |
SFTPB|6439 | 2.687e-34 | 4.83e-30 |
KRT19|3880 | 4.991e-34 | 8.98e-30 |
TM7SF4|81501 | 5.856e-34 | 1.05e-29 |
SERPINA1|5265 | 2.073e-33 | 3.73e-29 |
Figure S3. Get High-res Image As an example, this figure shows the association of ITGA3|3675 to 'HISTOLOGICAL.TYPE'. P value = 2.26e-37 with ANOVA analysis.

26 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S8. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 13 | |
YES | 400 | |
Significant markers | N = 26 | |
Higher in YES | 18 | |
Higher in NO | 8 |
Table S9. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
C14ORF180|400258 | 12.31 | 6.753e-14 | 1.21e-09 | 0.8788 |
FLJ37543|285668 | 14.21 | 2.111e-13 | 3.79e-09 | 0.8845 |
TAS2R43|259289 | 9.59 | 1.583e-11 | 2.84e-07 | 0.7814 |
ADIPOQ|9370 | 10.64 | 3.358e-11 | 6.03e-07 | 0.9115 |
HPR|3250 | 10.64 | 1.738e-09 | 3.12e-05 | 0.9232 |
LOC440173|440173 | 8.99 | 1.531e-08 | 0.000275 | 0.8827 |
ENPP3|5169 | 9 | 2.594e-08 | 0.000465 | 0.8582 |
CXORF48|54967 | 8.73 | 2.205e-07 | 0.00396 | 0.8335 |
C6ORF203|51250 | 8.56 | 3.197e-07 | 0.00574 | 0.876 |
HCFC1|3054 | -8.69 | 3.584e-07 | 0.00643 | 0.9002 |
Figure S4. Get High-res Image As an example, this figure shows the association of C14ORF180|400258 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 6.75e-14 with T-test analysis.

Table S10. Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'
RADIATIONEXPOSURE | Labels | N |
NO | 354 | |
YES | 16 | |
Significant markers | N = 6 | |
Higher in YES | 2 | |
Higher in NO | 4 |
Table S11. Get Full Table List of 6 genes differentially expressed by 'RADIATIONEXPOSURE'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
CRNN|49860 | -12.13 | 7.086e-21 | 1.27e-16 | 0.927 |
C13ORF30|144809 | -11.05 | 2.252e-19 | 4.05e-15 | 0.8687 |
CSNK1A1P|161635 | -7.71 | 2.612e-11 | 4.7e-07 | 0.8219 |
CYP2C9|1559 | -7.55 | 8.719e-11 | 1.57e-06 | 0.7341 |
CYORF15A|246126 | 6.56 | 1.31e-09 | 2.35e-05 | 0.606 |
EIF1AY|9086 | 5.43 | 3.311e-07 | 0.00595 | 0.7776 |
Figure S5. Get High-res Image As an example, this figure shows the association of CRNN|49860 to 'RADIATIONEXPOSURE'. P value = 7.09e-21 with T-test analysis.

Table S12. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'
DISTANT.METASTASIS | Labels | N |
M0 | 231 | |
M1 | 8 | |
MX | 173 | |
Significant markers | N = 8 |
Table S13. Get Full Table List of 8 genes differentially expressed by 'DISTANT.METASTASIS'
ANOVA_P | Q | |
---|---|---|
C4ORF6|10141 | 8.042e-08 | 0.00145 |
RNF207|388591 | 8.664e-08 | 0.00156 |
CYP21A2|1589 | 1.104e-07 | 0.00199 |
HSPA6|3310 | 5.558e-07 | 0.01 |
TAF1D|79101 | 9.498e-07 | 0.0171 |
SNORA8|654320 | 1.436e-06 | 0.0258 |
ADAMTS10|81794 | 2.04e-06 | 0.0367 |
PPP1R13L|10848 | 2.142e-06 | 0.0385 |
Figure S6. Get High-res Image As an example, this figure shows the association of C4ORF6|10141 to 'DISTANT.METASTASIS'. P value = 8.04e-08 with ANOVA analysis.

Table S14. Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'
EXTRATHYROIDAL.EXTENSION | Labels | N |
MINIMAL (T3) | 110 | |
MODERATE/ADVANCED (T4A) | 13 | |
NONE | 270 | |
VERY ADVANCED (T4B) | 1 | |
Significant markers | N = 639 |
Table S15. Get Full Table List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'
ANOVA_P | Q | |
---|---|---|
ASAH2|56624 | 4.689e-15 | 8.44e-11 |
FAM69C|125704 | 6.159e-14 | 1.11e-09 |
COL11A1|1301 | 5.794e-13 | 1.04e-08 |
FAM169A|26049 | 6.843e-13 | 1.23e-08 |
CYP26A1|1592 | 8.149e-13 | 1.47e-08 |
COL1A1|1277 | 1.103e-12 | 1.98e-08 |
FOXJ1|2302 | 1.186e-12 | 2.13e-08 |
SRPX2|27286 | 1.375e-12 | 2.47e-08 |
SLC25A42|284439 | 2.654e-12 | 4.77e-08 |
ZNF540|163255 | 3.772e-12 | 6.79e-08 |
Figure S7. Get High-res Image As an example, this figure shows the association of ASAH2|56624 to 'EXTRATHYROIDAL.EXTENSION'. P value = 4.69e-15 with ANOVA analysis.

Table S16. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 191 | |
N1 | 48 | |
N1A | 77 | |
N1B | 59 | |
NX | 38 | |
Significant markers | N = 1295 |
Table S17. Get Full Table List of top 10 genes differentially expressed by 'LYMPH.NODE.METASTASIS'
ANOVA_P | Q | |
---|---|---|
CREB5|9586 | 2.403e-15 | 4.32e-11 |
KCNN4|3783 | 2.297e-14 | 4.13e-10 |
ICAM1|3383 | 6.153e-14 | 1.11e-09 |
MLEC|9761 | 6.576e-14 | 1.18e-09 |
FN1|2335 | 7.421e-14 | 1.34e-09 |
CTSC|1075 | 9e-14 | 1.62e-09 |
SFTPB|6439 | 1.351e-13 | 2.43e-09 |
WFS1|7466 | 1.452e-13 | 2.61e-09 |
TMEM117|84216 | 2.118e-13 | 3.81e-09 |
PROS1|5627 | 2.435e-13 | 4.38e-09 |
Figure S8. Get High-res Image As an example, this figure shows the association of CREB5|9586 to 'LYMPH.NODE.METASTASIS'. P value = 2.4e-15 with ANOVA analysis.

Table S18. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 325 | |
R1 | 35 | |
R2 | 2 | |
RX | 26 | |
Significant markers | N = 1 |
Table S19. Get Full Table List of one gene differentially expressed by 'COMPLETENESS.OF.RESECTION'
ANOVA_P | Q | |
---|---|---|
CATSPER2P1|440278 | 3.665e-09 | 6.6e-05 |
Figure S9. Get High-res Image As an example, this figure shows the association of CATSPER2P1|440278 to 'COMPLETENESS.OF.RESECTION'. P value = 3.66e-09 with ANOVA analysis.

Table S20. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'
NUMBER.OF.LYMPH.NODES | Mean (SD) | 3.57 (6.3) |
Significant markers | N = 673 | |
pos. correlated | 377 | |
neg. correlated | 296 |
Table S21. Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
CBFB|865 | 0.3887 | 6.519e-13 | 1.17e-08 |
PELI1|57162 | 0.3859 | 9.801e-13 | 1.76e-08 |
FAM60A|58516 | 0.3824 | 1.635e-12 | 2.94e-08 |
ZNF346|23567 | -0.3766 | 3.725e-12 | 6.7e-08 |
CREB5|9586 | 0.3751 | 4.644e-12 | 8.35e-08 |
CSGALNACT2|55454 | 0.3725 | 6.661e-12 | 1.2e-07 |
CCDC109B|55013 | 0.3692 | 1.043e-11 | 1.88e-07 |
TAGLN2|8407 | 0.3679 | 1.25e-11 | 2.25e-07 |
S100A10|6281 | 0.3613 | 3.056e-11 | 5.5e-07 |
TMEM117|84216 | 0.3592 | 4.067e-11 | 7.31e-07 |
Figure S10. Get High-res Image As an example, this figure shows the association of CBFB|865 to 'NUMBER.OF.LYMPH.NODES'. P value = 6.52e-13 with Spearman correlation analysis. The straight line presents the best linear regression.

Table S22. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'
NEOPLASM.DISEASESTAGE | Labels | N |
STAGE I | 232 | |
STAGE II | 46 | |
STAGE III | 90 | |
STAGE IV | 2 | |
STAGE IVA | 35 | |
STAGE IVC | 5 | |
Significant markers | N = 263 |
Table S23. Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'
ANOVA_P | Q | |
---|---|---|
GSPT2|23708 | 7.713e-17 | 1.39e-12 |
SEMA3G|56920 | 1.011e-13 | 1.82e-09 |
FAM50B|26240 | 1.409e-13 | 2.53e-09 |
GJA5|2702 | 1.119e-11 | 2.01e-07 |
MOGS|7841 | 1.653e-11 | 2.97e-07 |
CYP26A1|1592 | 2.764e-11 | 4.97e-07 |
HARS2|23438 | 1.316e-10 | 2.37e-06 |
ZNF518B|85460 | 4.636e-10 | 8.34e-06 |
PECI|10455 | 5.139e-10 | 9.24e-06 |
MKKS|8195 | 1.377e-09 | 2.48e-05 |
Figure S11. Get High-res Image As an example, this figure shows the association of GSPT2|23708 to 'NEOPLASM.DISEASESTAGE'. P value = 7.71e-17 with ANOVA analysis.

Table S24. Basic characteristics of clinical feature: 'MULTIFOCALITY'
MULTIFOCALITY | Labels | N |
MULTIFOCAL | 177 | |
UNIFOCAL | 227 | |
Significant markers | N = 1 | |
Higher in UNIFOCAL | 0 | |
Higher in MULTIFOCAL | 1 |
Table S25. Get Full Table List of one gene differentially expressed by 'MULTIFOCALITY'
T(pos if higher in 'UNIFOCAL') | ttestP | Q | AUC | |
---|---|---|---|---|
TMTC1|83857 | -4.77 | 2.571e-06 | 0.0463 | 0.6369 |
Figure S12. Get High-res Image As an example, this figure shows the association of TMTC1|83857 to 'MULTIFOCALITY'. P value = 2.57e-06 with T-test analysis.

Table S26. Basic characteristics of clinical feature: 'TUMOR.SIZE'
TUMOR.SIZE | Mean (SD) | 2.92 (1.6) |
Significant markers | N = 7 | |
pos. correlated | 0 | |
neg. correlated | 7 |
Table S27. Get Full Table List of 7 genes significantly correlated to 'TUMOR.SIZE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
CLDN2|9075 | -0.2914 | 1.014e-07 | 0.00183 |
ZC3H10|84872 | -0.279 | 3.198e-07 | 0.00575 |
C3ORF32|51066 | -0.2746 | 6.844e-07 | 0.0123 |
PI16|221476 | -0.2718 | 8.584e-07 | 0.0154 |
FOXI2|399823 | -0.2644 | 1.501e-06 | 0.027 |
LOC151162|151162 | -0.2628 | 1.551e-06 | 0.0279 |
SEC22A|26984 | -0.2571 | 2.648e-06 | 0.0476 |
Figure S13. Get High-res Image As an example, this figure shows the association of CLDN2|9075 to 'TUMOR.SIZE'. P value = 1.01e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

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Expresson data file = THCA-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = THCA-TP.clin.merged.picked.txt
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Number of patients = 413
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Number of genes = 17995
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Number of clinical features = 14
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.