This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.
Testing the association between subtypes identified by 24 different clustering approaches and 15 clinical features across 284 patients, 15 significant findings detected with Q value < 0.25.
-
2 subtypes identified in current cancer cohort by 'Del Peak 2(2p22.3) mutation analysis'. These subtypes correlate to 'NUMBER.OF.LYMPH.NODES'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 3(2q35) mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE', 'NUMBER.OF.LYMPH.NODES', and 'NEOPLASM.DISEASESTAGE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 5(6q22.31) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 6(6q27) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 8(7q34) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 10(8q24.22) mutation analysis'. These subtypes correlate to 'NUMBER.OF.LYMPH.NODES'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 11(9p21.3) mutation analysis'. These subtypes correlate to 'NEOPLASM.DISEASESTAGE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 12(9q22.32) mutation analysis'. These subtypes correlate to 'NEOPLASM.DISEASESTAGE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 13(10q21.2) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 14(10q23.31) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 15(11p15.1) mutation analysis'. These subtypes correlate to 'NUMBER.OF.LYMPH.NODES'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 16(13q12.3) mutation analysis'. These subtypes correlate to 'RADIATIONEXPOSURE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 17(13q14.3) mutation analysis'. These subtypes correlate to 'RADIATIONEXPOSURE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 18(15q25.3) mutation analysis'. These subtypes correlate to 'NUMBER.OF.LYMPH.NODES'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 20(16q23.3) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 21(17p13.1) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 22(18p11.21) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 23(19p13.2) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 26(21q21.1) mutation analysis'. These subtypes correlate to 'NEOPLASM.DISEASESTAGE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 27(22q13.31) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 28(22q13.2) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 29(22q13.32) mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by 'Del Peak 30(Xq22.1) mutation analysis'. These subtypes correlate to 'NEOPLASM.DISEASESTAGE'.
-
2 subtypes identified in current cancer cohort by 'Del Peak 31(Xq22.3) mutation analysis'. These subtypes correlate to 'NUMBER.OF.LYMPH.NODES' and 'NEOPLASM.DISEASESTAGE'.
Table 1. Get Full Table Overview of the association between subtypes identified by 24 different clustering approaches and 15 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 15 significant findings detected.
Clinical Features |
Time to Death |
AGE | GENDER |
HISTOLOGICAL TYPE |
RADIATIONS RADIATION REGIMENINDICATION |
RADIATIONEXPOSURE |
DISTANT METASTASIS |
EXTRATHYROIDAL EXTENSION |
LYMPH NODE METASTASIS |
COMPLETENESS OF RESECTION |
NUMBER OF LYMPH NODES |
TUMOR STAGECODE |
NEOPLASM DISEASESTAGE |
MULTIFOCALITY |
TUMOR SIZE |
Statistical Tests | logrank test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Chi-square test | Fisher's exact test | t-test | t-test | Chi-square test | Fisher's exact test | t-test |
Del Peak 2(2p22 3) |
1 (1.00) |
0.157 (1.00) |
0.455 (1.00) |
0.019 (1.00) |
1 (1.00) |
1 (1.00) |
0.391 (1.00) |
0.258 (1.00) |
0.135 (1.00) |
0.788 (1.00) |
2.86e-14 (9.52e-12) |
0.00102 (0.325) |
0.749 (1.00) |
0.688 (1.00) |
|
Del Peak 3(2q35) |
1 (1.00) |
0.0123 (1.00) |
0.684 (1.00) |
0.000323 (0.104) |
1 (1.00) |
1 (1.00) |
0.382 (1.00) |
0.729 (1.00) |
0.182 (1.00) |
0.25 (1.00) |
2.91e-14 (9.67e-12) |
0.00014 (0.0453) |
1 (1.00) |
0.185 (1.00) |
|
Del Peak 5(6q22 31) |
0.00468 (1.00) |
0.197 (1.00) |
1 (1.00) |
0.802 (1.00) |
0.184 (1.00) |
1 (1.00) |
0.18 (1.00) |
0.606 (1.00) |
0.769 (1.00) |
1 (1.00) |
0.00663 (1.00) |
0.0718 (1.00) |
0.37 (1.00) |
0.033 (1.00) |
|
Del Peak 6(6q27) |
0.00468 (1.00) |
0.197 (1.00) |
1 (1.00) |
0.802 (1.00) |
0.184 (1.00) |
1 (1.00) |
0.18 (1.00) |
0.606 (1.00) |
0.769 (1.00) |
1 (1.00) |
0.00663 (1.00) |
0.0718 (1.00) |
0.37 (1.00) |
0.033 (1.00) |
|
Del Peak 8(7q34) |
1 (1.00) |
0.759 (1.00) |
1 (1.00) |
0.251 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.606 (1.00) |
0.769 (1.00) |
1 (1.00) |
0.374 (1.00) |
0.7 (1.00) |
0.37 (1.00) |
0.23 (1.00) |
|
Del Peak 10(8q24 22) |
1 (1.00) |
0.0567 (1.00) |
0.109 (1.00) |
0.0294 (1.00) |
1 (1.00) |
1 (1.00) |
0.682 (1.00) |
1 (1.00) |
0.464 (1.00) |
0.575 (1.00) |
3.08e-14 (1.01e-11) |
0.00506 (1.00) |
0.684 (1.00) |
0.185 (1.00) |
|
Del Peak 11(9p21 3) |
1 (1.00) |
0.0401 (1.00) |
0.682 (1.00) |
0.627 (1.00) |
1 (1.00) |
1 (1.00) |
0.519 (1.00) |
0.3 (1.00) |
0.309 (1.00) |
0.309 (1.00) |
0.00238 (0.755) |
1.88e-05 (0.00612) |
0.282 (1.00) |
0.124 (1.00) |
|
Del Peak 12(9q22 32) |
1 (1.00) |
0.124 (1.00) |
1 (1.00) |
0.239 (1.00) |
0.402 (1.00) |
0.34 (1.00) |
0.302 (1.00) |
0.553 (1.00) |
0.101 (1.00) |
0.822 (1.00) |
0.373 (1.00) |
8.59e-05 (0.0279) |
1 (1.00) |
0.833 (1.00) |
|
Del Peak 13(10q21 2) |
1 (1.00) |
0.565 (1.00) |
1 (1.00) |
0.0672 (1.00) |
0.301 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.585 (1.00) |
0.699 (1.00) |
0.293 (1.00) |
0.618 (1.00) |
1 (1.00) |
0.0236 (1.00) |
|
Del Peak 14(10q23 31) |
1 (1.00) |
0.0207 (1.00) |
0.428 (1.00) |
0.0242 (1.00) |
1 (1.00) |
1 (1.00) |
0.765 (1.00) |
0.729 (1.00) |
0.219 (1.00) |
1 (1.00) |
0.0584 (1.00) |
0.0117 (1.00) |
0.723 (1.00) |
0.0374 (1.00) |
|
Del Peak 15(11p15 1) |
0.00468 (1.00) |
0.031 (1.00) |
0.273 (1.00) |
0.145 (1.00) |
0.184 (1.00) |
1 (1.00) |
0.18 (1.00) |
0.606 (1.00) |
0.36 (1.00) |
0.494 (1.00) |
3.02e-14 (1e-11) |
0.515 (1.00) |
0.622 (1.00) |
0.238 (1.00) |
|
Del Peak 16(13q12 3) |
0.00468 (1.00) |
0.0131 (1.00) |
0.131 (1.00) |
0.108 (1.00) |
0.402 (1.00) |
0.000241 (0.0777) |
0.302 (1.00) |
0.553 (1.00) |
0.277 (1.00) |
0.488 (1.00) |
0.0311 (1.00) |
0.118 (1.00) |
0.749 (1.00) |
0.137 (1.00) |
|
Del Peak 17(13q14 3) |
0.00468 (1.00) |
0.177 (1.00) |
0.33 (1.00) |
0.162 (1.00) |
0.129 (1.00) |
0.000601 (0.192) |
0.441 (1.00) |
0.446 (1.00) |
0.0996 (1.00) |
1 (1.00) |
0.0358 (1.00) |
0.535 (1.00) |
0.377 (1.00) |
0.353 (1.00) |
|
Del Peak 18(15q25 3) |
1 (1.00) |
0.247 (1.00) |
0.575 (1.00) |
0.145 (1.00) |
1 (1.00) |
1 (1.00) |
0.18 (1.00) |
1 (1.00) |
0.36 (1.00) |
0.494 (1.00) |
3.02e-14 (1e-11) |
0.0489 (1.00) |
0.622 (1.00) |
0.626 (1.00) |
|
Del Peak 20(16q23 3) |
1 (1.00) |
0.323 (1.00) |
0.572 (1.00) |
0.0221 (1.00) |
1 (1.00) |
0.128 (1.00) |
1 (1.00) |
0.192 (1.00) |
0.708 (1.00) |
0.4 (1.00) |
0.0561 (1.00) |
0.139 (1.00) |
1 (1.00) |
||
Del Peak 21(17p13 1) |
1 (1.00) |
0.944 (1.00) |
0.333 (1.00) |
0.367 (1.00) |
0.0208 (1.00) |
1 (1.00) |
0.429 (1.00) |
0.102 (1.00) |
0.215 (1.00) |
1 (1.00) |
0.293 (1.00) |
0.211 (1.00) |
0.214 (1.00) |
0.306 (1.00) |
|
Del Peak 22(18p11 21) |
1 (1.00) |
0.958 (1.00) |
0.572 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.865 (1.00) |
1 (1.00) |
0.0561 (1.00) |
0.0502 (1.00) |
0.622 (1.00) |
0.976 (1.00) |
|
Del Peak 23(19p13 2) |
1 (1.00) |
0.0248 (1.00) |
1 (1.00) |
0.145 (1.00) |
1 (1.00) |
1 (1.00) |
0.604 (1.00) |
1 (1.00) |
0.105 (1.00) |
0.4 (1.00) |
0.722 (1.00) |
0.37 (1.00) |
|||
Del Peak 26(21q21 1) |
1 (1.00) |
0.0042 (1.00) |
1 (1.00) |
0.447 (1.00) |
1 (1.00) |
1 (1.00) |
0.519 (1.00) |
1 (1.00) |
0.334 (1.00) |
0.201 (1.00) |
0.946 (1.00) |
0.000339 (0.109) |
1 (1.00) |
0.73 (1.00) |
|
Del Peak 27(22q13 31) |
0.724 (1.00) |
0.748 (1.00) |
0.719 (1.00) |
0.0552 (1.00) |
0.477 (1.00) |
0.695 (1.00) |
0.63 (1.00) |
0.509 (1.00) |
0.644 (1.00) |
0.4 (1.00) |
0.684 (1.00) |
0.854 (1.00) |
0.109 (1.00) |
0.305 (1.00) |
|
Del Peak 28(22q13 2) |
0.724 (1.00) |
0.748 (1.00) |
0.719 (1.00) |
0.0552 (1.00) |
0.477 (1.00) |
0.695 (1.00) |
0.63 (1.00) |
0.509 (1.00) |
0.644 (1.00) |
0.4 (1.00) |
0.684 (1.00) |
0.854 (1.00) |
0.109 (1.00) |
0.305 (1.00) |
|
Del Peak 29(22q13 32) |
0.724 (1.00) |
0.798 (1.00) |
0.595 (1.00) |
0.0314 (1.00) |
0.476 (1.00) |
0.695 (1.00) |
0.722 (1.00) |
0.509 (1.00) |
0.587 (1.00) |
0.4 (1.00) |
0.607 (1.00) |
0.882 (1.00) |
0.0799 (1.00) |
0.305 (1.00) |
|
Del Peak 30(Xq22 1) |
1 (1.00) |
0.177 (1.00) |
0.0397 (1.00) |
0.135 (1.00) |
1 (1.00) |
0.204 (1.00) |
0.295 (1.00) |
0.411 (1.00) |
0.382 (1.00) |
0.246 (1.00) |
0.691 (1.00) |
0.000772 (0.246) |
0.684 (1.00) |
0.682 (1.00) |
|
Del Peak 31(Xq22 3) |
1 (1.00) |
0.0642 (1.00) |
0.0536 (1.00) |
0.206 (1.00) |
1 (1.00) |
0.128 (1.00) |
0.18 (1.00) |
0.606 (1.00) |
0.36 (1.00) |
0.494 (1.00) |
3.02e-14 (1e-11) |
2.08e-06 (0.000679) |
1 (1.00) |
0.515 (1.00) |
Table S1. Description of clustering approach #1: 'Del Peak 2(2p22.3) mutation analysis'
Cluster Labels | DEL PEAK 2(2P22.3) MUTATED | DEL PEAK 2(2P22.3) WILD-TYPE |
---|---|---|
Number of samples | 9 | 275 |
P value = 2.86e-14 (t-test), Q value = 9.5e-12
Table S2. Clustering Approach #1: 'Del Peak 2(2p22.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 2(2P22.3) MUTATED | 7 | 0.0 (0.0) |
DEL PEAK 2(2P22.3) WILD-TYPE | 218 | 2.9 (5.3) |
Figure S1. Get High-res Image Clustering Approach #1: 'Del Peak 2(2p22.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Table S3. Description of clustering approach #2: 'Del Peak 3(2q35) mutation analysis'
Cluster Labels | DEL PEAK 3(2Q35) MUTATED | DEL PEAK 3(2Q35) WILD-TYPE |
---|---|---|
Number of samples | 8 | 276 |
P value = 0.000323 (Fisher's exact test), Q value = 0.1
Table S4. Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'
nPatients | OTHER | THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) |
---|---|---|---|---|
ALL | 18 | 167 | 69 | 30 |
DEL PEAK 3(2Q35) MUTATED | 4 | 1 | 3 | 0 |
DEL PEAK 3(2Q35) WILD-TYPE | 14 | 166 | 66 | 30 |
Figure S2. Get High-res Image Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #4: 'HISTOLOGICAL.TYPE'

P value = 2.91e-14 (t-test), Q value = 9.7e-12
Table S5. Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 3(2Q35) MUTATED | 6 | 0.0 (0.0) |
DEL PEAK 3(2Q35) WILD-TYPE | 219 | 2.9 (5.3) |
Figure S3. Get High-res Image Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

P value = 0.00014 (Chi-square test), Q value = 0.045
Table S6. Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 3(2Q35) MUTATED | 1 | 5 | 2 | 0 | 0 |
DEL PEAK 3(2Q35) WILD-TYPE | 160 | 27 | 60 | 25 | 3 |
Figure S4. Get High-res Image Clustering Approach #2: 'Del Peak 3(2q35) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

Table S7. Description of clustering approach #3: 'Del Peak 5(6q22.31) mutation analysis'
Cluster Labels | DEL PEAK 5(6Q22.31) MUTATED | DEL PEAK 5(6Q22.31) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
Table S8. Description of clustering approach #4: 'Del Peak 6(6q27) mutation analysis'
Cluster Labels | DEL PEAK 6(6Q27) MUTATED | DEL PEAK 6(6Q27) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
Table S9. Description of clustering approach #5: 'Del Peak 8(7q34) mutation analysis'
Cluster Labels | DEL PEAK 8(7Q34) MUTATED | DEL PEAK 8(7Q34) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
Table S10. Description of clustering approach #6: 'Del Peak 10(8q24.22) mutation analysis'
Cluster Labels | DEL PEAK 10(8Q24.22) MUTATED | DEL PEAK 10(8Q24.22) WILD-TYPE |
---|---|---|
Number of samples | 5 | 279 |
P value = 3.08e-14 (t-test), Q value = 1e-11
Table S11. Clustering Approach #6: 'Del Peak 10(8q24.22) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 10(8Q24.22) MUTATED | 3 | 0.0 (0.0) |
DEL PEAK 10(8Q24.22) WILD-TYPE | 222 | 2.9 (5.3) |
Figure S5. Get High-res Image Clustering Approach #6: 'Del Peak 10(8q24.22) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Table S12. Description of clustering approach #7: 'Del Peak 11(9p21.3) mutation analysis'
Cluster Labels | DEL PEAK 11(9P21.3) MUTATED | DEL PEAK 11(9P21.3) WILD-TYPE |
---|---|---|
Number of samples | 7 | 277 |
P value = 1.88e-05 (Chi-square test), Q value = 0.0061
Table S13. Clustering Approach #7: 'Del Peak 11(9p21.3) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 11(9P21.3) MUTATED | 1 | 5 | 0 | 1 | 0 |
DEL PEAK 11(9P21.3) WILD-TYPE | 160 | 27 | 62 | 24 | 3 |
Figure S6. Get High-res Image Clustering Approach #7: 'Del Peak 11(9p21.3) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

Table S14. Description of clustering approach #8: 'Del Peak 12(9q22.32) mutation analysis'
Cluster Labels | DEL PEAK 12(9Q22.32) MUTATED | DEL PEAK 12(9Q22.32) WILD-TYPE |
---|---|---|
Number of samples | 10 | 274 |
P value = 8.59e-05 (Chi-square test), Q value = 0.028
Table S15. Clustering Approach #8: 'Del Peak 12(9q22.32) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 12(9Q22.32) MUTATED | 2 | 5 | 0 | 3 | 0 |
DEL PEAK 12(9Q22.32) WILD-TYPE | 159 | 27 | 62 | 22 | 3 |
Figure S7. Get High-res Image Clustering Approach #8: 'Del Peak 12(9q22.32) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

Table S16. Description of clustering approach #9: 'Del Peak 13(10q21.2) mutation analysis'
Cluster Labels | DEL PEAK 13(10Q21.2) MUTATED | DEL PEAK 13(10Q21.2) WILD-TYPE |
---|---|---|
Number of samples | 7 | 277 |
Table S17. Description of clustering approach #10: 'Del Peak 14(10q23.31) mutation analysis'
Cluster Labels | DEL PEAK 14(10Q23.31) MUTATED | DEL PEAK 14(10Q23.31) WILD-TYPE |
---|---|---|
Number of samples | 8 | 276 |
Table S18. Description of clustering approach #11: 'Del Peak 15(11p15.1) mutation analysis'
Cluster Labels | DEL PEAK 15(11P15.1) MUTATED | DEL PEAK 15(11P15.1) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
P value = 3.02e-14 (t-test), Q value = 1e-11
Table S19. Clustering Approach #11: 'Del Peak 15(11p15.1) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 15(11P15.1) MUTATED | 4 | 0.0 (0.0) |
DEL PEAK 15(11P15.1) WILD-TYPE | 221 | 2.9 (5.3) |
Figure S8. Get High-res Image Clustering Approach #11: 'Del Peak 15(11p15.1) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Table S20. Description of clustering approach #12: 'Del Peak 16(13q12.3) mutation analysis'
Cluster Labels | DEL PEAK 16(13Q12.3) MUTATED | DEL PEAK 16(13Q12.3) WILD-TYPE |
---|---|---|
Number of samples | 10 | 274 |
P value = 0.000241 (Fisher's exact test), Q value = 0.078
Table S21. Clustering Approach #12: 'Del Peak 16(13q12.3) mutation analysis' versus Clinical Feature #6: 'RADIATIONEXPOSURE'
nPatients | NO | YES |
---|---|---|
ALL | 237 | 11 |
DEL PEAK 16(13Q12.3) MUTATED | 5 | 4 |
DEL PEAK 16(13Q12.3) WILD-TYPE | 232 | 7 |
Figure S9. Get High-res Image Clustering Approach #12: 'Del Peak 16(13q12.3) mutation analysis' versus Clinical Feature #6: 'RADIATIONEXPOSURE'

Table S22. Description of clustering approach #13: 'Del Peak 17(13q14.3) mutation analysis'
Cluster Labels | DEL PEAK 17(13Q14.3) MUTATED | DEL PEAK 17(13Q14.3) WILD-TYPE |
---|---|---|
Number of samples | 13 | 271 |
P value = 0.000601 (Fisher's exact test), Q value = 0.19
Table S23. Clustering Approach #13: 'Del Peak 17(13q14.3) mutation analysis' versus Clinical Feature #6: 'RADIATIONEXPOSURE'
nPatients | NO | YES |
---|---|---|
ALL | 237 | 11 |
DEL PEAK 17(13Q14.3) MUTATED | 7 | 4 |
DEL PEAK 17(13Q14.3) WILD-TYPE | 230 | 7 |
Figure S10. Get High-res Image Clustering Approach #13: 'Del Peak 17(13q14.3) mutation analysis' versus Clinical Feature #6: 'RADIATIONEXPOSURE'

Table S24. Description of clustering approach #14: 'Del Peak 18(15q25.3) mutation analysis'
Cluster Labels | DEL PEAK 18(15Q25.3) MUTATED | DEL PEAK 18(15Q25.3) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
P value = 3.02e-14 (t-test), Q value = 1e-11
Table S25. Clustering Approach #14: 'Del Peak 18(15q25.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 18(15Q25.3) MUTATED | 4 | 0.0 (0.0) |
DEL PEAK 18(15Q25.3) WILD-TYPE | 221 | 2.9 (5.3) |
Figure S11. Get High-res Image Clustering Approach #14: 'Del Peak 18(15q25.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

Table S26. Description of clustering approach #15: 'Del Peak 20(16q23.3) mutation analysis'
Cluster Labels | DEL PEAK 20(16Q23.3) MUTATED | DEL PEAK 20(16Q23.3) WILD-TYPE |
---|---|---|
Number of samples | 3 | 281 |
Table S27. Description of clustering approach #16: 'Del Peak 21(17p13.1) mutation analysis'
Cluster Labels | DEL PEAK 21(17P13.1) MUTATED | DEL PEAK 21(17P13.1) WILD-TYPE |
---|---|---|
Number of samples | 5 | 279 |
Table S28. Description of clustering approach #17: 'Del Peak 22(18p11.21) mutation analysis'
Cluster Labels | DEL PEAK 22(18P11.21) MUTATED | DEL PEAK 22(18P11.21) WILD-TYPE |
---|---|---|
Number of samples | 3 | 281 |
Table S29. Description of clustering approach #18: 'Del Peak 23(19p13.2) mutation analysis'
Cluster Labels | DEL PEAK 23(19P13.2) MUTATED | DEL PEAK 23(19P13.2) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
Table S30. Description of clustering approach #19: 'Del Peak 26(21q21.1) mutation analysis'
Cluster Labels | DEL PEAK 26(21Q21.1) MUTATED | DEL PEAK 26(21Q21.1) WILD-TYPE |
---|---|---|
Number of samples | 7 | 277 |
P value = 0.000339 (Chi-square test), Q value = 0.11
Table S31. Clustering Approach #19: 'Del Peak 26(21q21.1) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 26(21Q21.1) MUTATED | 0 | 4 | 1 | 2 | 0 |
DEL PEAK 26(21Q21.1) WILD-TYPE | 161 | 28 | 61 | 23 | 3 |
Figure S12. Get High-res Image Clustering Approach #19: 'Del Peak 26(21q21.1) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

Table S32. Description of clustering approach #20: 'Del Peak 27(22q13.31) mutation analysis'
Cluster Labels | DEL PEAK 27(22Q13.31) MUTATED | DEL PEAK 27(22Q13.31) WILD-TYPE |
---|---|---|
Number of samples | 49 | 235 |
Table S33. Description of clustering approach #21: 'Del Peak 28(22q13.2) mutation analysis'
Cluster Labels | DEL PEAK 28(22Q13.2) MUTATED | DEL PEAK 28(22Q13.2) WILD-TYPE |
---|---|---|
Number of samples | 49 | 235 |
Table S34. Description of clustering approach #22: 'Del Peak 29(22q13.32) mutation analysis'
Cluster Labels | DEL PEAK 29(22Q13.32) MUTATED | DEL PEAK 29(22Q13.32) WILD-TYPE |
---|---|---|
Number of samples | 50 | 234 |
Table S35. Description of clustering approach #23: 'Del Peak 30(Xq22.1) mutation analysis'
Cluster Labels | DEL PEAK 30(XQ22.1) MUTATED | DEL PEAK 30(XQ22.1) WILD-TYPE |
---|---|---|
Number of samples | 6 | 278 |
P value = 0.000772 (Chi-square test), Q value = 0.25
Table S36. Clustering Approach #23: 'Del Peak 30(Xq22.1) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 30(XQ22.1) MUTATED | 1 | 4 | 1 | 0 | 0 |
DEL PEAK 30(XQ22.1) WILD-TYPE | 160 | 28 | 61 | 25 | 3 |
Figure S13. Get High-res Image Clustering Approach #23: 'Del Peak 30(Xq22.1) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

Table S37. Description of clustering approach #24: 'Del Peak 31(Xq22.3) mutation analysis'
Cluster Labels | DEL PEAK 31(XQ22.3) MUTATED | DEL PEAK 31(XQ22.3) WILD-TYPE |
---|---|---|
Number of samples | 4 | 280 |
P value = 3.02e-14 (t-test), Q value = 1e-11
Table S38. Clustering Approach #24: 'Del Peak 31(Xq22.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 225 | 2.8 (5.2) |
DEL PEAK 31(XQ22.3) MUTATED | 4 | 0.0 (0.0) |
DEL PEAK 31(XQ22.3) WILD-TYPE | 221 | 2.9 (5.3) |
Figure S14. Get High-res Image Clustering Approach #24: 'Del Peak 31(Xq22.3) mutation analysis' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'

P value = 2.08e-06 (Chi-square test), Q value = 0.00068
Table S39. Clustering Approach #24: 'Del Peak 31(Xq22.3) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'
nPatients | STAGE I | STAGE II | STAGE III | STAGE IVA | STAGE IVC |
---|---|---|---|---|---|
ALL | 161 | 32 | 62 | 25 | 3 |
DEL PEAK 31(XQ22.3) MUTATED | 0 | 4 | 0 | 0 | 0 |
DEL PEAK 31(XQ22.3) WILD-TYPE | 161 | 28 | 62 | 25 | 3 |
Figure S15. Get High-res Image Clustering Approach #24: 'Del Peak 31(Xq22.3) mutation analysis' versus Clinical Feature #13: 'NEOPLASM.DISEASESTAGE'

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Cluster data file = all_lesions.conf_99.cnv.cluster.txt
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Clinical data file = THCA-TP.clin.merged.picked.txt
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Number of patients = 284
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Number of clustering approaches = 24
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Number of selected clinical features = 15
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Exclude small clusters that include fewer than K patients, K = 3
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R
For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between two tumor subtypes using 't.test' function in R
For binary clinical features, two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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.