This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.
Testing the association between copy number variation 20 focal events and 5 clinical features across 191 patients, 11 significant findings detected with Q value < 0.25.
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amp_1q43 cnv correlated to 'YEARS_TO_BIRTH'.
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amp_11q23.3 cnv correlated to 'YEARS_TO_BIRTH'.
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amp_21q22.2 cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
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del_3p13 cnv correlated to 'Time to Death'.
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del_5q31.2 cnv correlated to 'Time to Death' and 'YEARS_TO_BIRTH'.
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del_12p13.2 cnv correlated to 'Time to Death'.
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del_17q11.2 cnv correlated to 'Time to Death'.
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del_18p11.21 cnv correlated to 'Time to Death'.
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del_20q13.13 cnv correlated to 'Time to Death'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 20 focal events and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 11 significant findings detected.
Clinical Features |
Time to Death |
YEARS TO BIRTH |
GENDER | RACE | ETHNICITY | ||
nCNV (%) | nWild-Type | logrank test | Wilcoxon-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
amp 21q22 2 | 14 (7%) | 177 |
0.00622 (0.19) |
0.0236 (0.215) |
0.0922 (0.464) |
0.383 (0.782) |
1 (1.00) |
del 5q31 2 | 18 (9%) | 173 |
0.0179 (0.209) |
0.0108 (0.19) |
0.0464 (0.357) |
1 (1.00) |
1 (1.00) |
amp 1q43 | 7 (4%) | 184 |
0.194 (0.613) |
0.0209 (0.209) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
amp 11q23 3 | 17 (9%) | 174 |
0.137 (0.527) |
0.0171 (0.209) |
0.45 (0.865) |
1 (1.00) |
0.249 (0.663) |
del 3p13 | 8 (4%) | 183 |
0.000606 (0.0606) |
0.112 (0.485) |
0.295 (0.74) |
0.0976 (0.464) |
1 (1.00) |
del 12p13 2 | 10 (5%) | 181 |
0.00127 (0.0636) |
0.367 (0.781) |
0.351 (0.781) |
1 (1.00) |
1 (1.00) |
del 17q11 2 | 13 (7%) | 178 |
0.0103 (0.19) |
0.321 (0.764) |
0.775 (1.00) |
0.652 (1.00) |
1 (1.00) |
del 18p11 21 | 9 (5%) | 182 |
0.0199 (0.209) |
0.427 (0.838) |
0.185 (0.613) |
0.557 (0.963) |
1 (1.00) |
del 20q13 13 | 4 (2%) | 187 |
0.0114 (0.19) |
0.0674 (0.397) |
0.627 (1.00) |
0.3 (0.74) |
1 (1.00) |
amp 1p33 | 7 (4%) | 184 |
0.202 (0.613) |
0.119 (0.497) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
amp 13q31 3 | 7 (4%) | 184 |
0.84 (1.00) |
0.0648 (0.397) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
amp 19p13 2 | 6 (3%) | 185 |
0.701 (1.00) |
0.793 (1.00) |
0.223 (0.655) |
1 (1.00) |
1 (1.00) |
amp 20q11 21 | 3 (2%) | 188 |
0.184 (0.613) |
0.346 (0.781) |
0.252 (0.663) |
0.234 (0.663) |
1 (1.00) |
del 7p12 1 | 16 (8%) | 175 |
0.166 (0.613) |
0.484 (0.914) |
0.604 (1.00) |
1 (1.00) |
1 (1.00) |
del 7q34 | 24 (13%) | 167 |
0.102 (0.464) |
0.197 (0.613) |
0.512 (0.917) |
0.769 (1.00) |
1 (1.00) |
del 7q34 | 24 (13%) | 167 |
0.102 (0.464) |
0.197 (0.613) |
0.512 (0.917) |
0.769 (1.00) |
1 (1.00) |
del 9q21 32 | 5 (3%) | 186 |
0.735 (1.00) |
0.417 (0.834) |
0.378 (0.782) |
0.364 (0.781) |
1 (1.00) |
del 12q21 33 | 3 (2%) | 188 |
0.367 (0.781) |
0.0366 (0.305) |
0.252 (0.663) |
1 (1.00) |
1 (1.00) |
del 16q23 1 | 9 (5%) | 182 |
0.0992 (0.464) |
0.304 (0.74) |
0.513 (0.917) |
0.559 (0.963) |
1 (1.00) |
del 17p13 2 | 15 (8%) | 176 |
0.0528 (0.377) |
0.129 (0.516) |
0.0565 (0.377) |
0.671 (1.00) |
1 (1.00) |
P value = 0.0209 (Wilcoxon-test), Q value = 0.21
Table S1. Gene #2: 'amp_1q43' versus Clinical Feature #2: 'YEARS_TO_BIRTH'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
AMP PEAK 2(1Q43) MUTATED | 7 | 67.6 (11.3) |
AMP PEAK 2(1Q43) WILD-TYPE | 184 | 54.8 (16.1) |
Figure S1. Get High-res Image Gene #2: 'amp_1q43' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

P value = 0.0171 (Wilcoxon-test), Q value = 0.21
Table S2. Gene #3: 'amp_11q23.3' versus Clinical Feature #2: 'YEARS_TO_BIRTH'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
AMP PEAK 3(11Q23.3) MUTATED | 17 | 63.3 (12.1) |
AMP PEAK 3(11Q23.3) WILD-TYPE | 174 | 54.4 (16.2) |
Figure S2. Get High-res Image Gene #3: 'amp_11q23.3' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

P value = 0.00622 (logrank test), Q value = 0.19
Table S3. Gene #7: 'amp_21q22.2' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
AMP PEAK 7(21Q22.2) MUTATED | 12 | 10 | 1.0 - 24.0 (5.5) |
AMP PEAK 7(21Q22.2) WILD-TYPE | 166 | 106 | 0.0 - 94.1 (12.0) |
Figure S3. Get High-res Image Gene #7: 'amp_21q22.2' versus Clinical Feature #1: 'Time to Death'

P value = 0.0236 (Wilcoxon-test), Q value = 0.21
Table S4. Gene #7: 'amp_21q22.2' versus Clinical Feature #2: 'YEARS_TO_BIRTH'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
AMP PEAK 7(21Q22.2) MUTATED | 14 | 63.7 (16.7) |
AMP PEAK 7(21Q22.2) WILD-TYPE | 177 | 54.6 (15.9) |
Figure S4. Get High-res Image Gene #7: 'amp_21q22.2' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

P value = 0.000606 (logrank test), Q value = 0.061
Table S5. Gene #8: 'del_3p13' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 2(3P13) MUTATED | 8 | 7 | 0.0 - 14.0 (1.5) |
DEL PEAK 2(3P13) WILD-TYPE | 170 | 109 | 0.0 - 94.1 (12.0) |
Figure S5. Get High-res Image Gene #8: 'del_3p13' versus Clinical Feature #1: 'Time to Death'

P value = 0.0179 (logrank test), Q value = 0.21
Table S6. Gene #9: 'del_5q31.2' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
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ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 3(5Q31.2) MUTATED | 17 | 15 | 1.0 - 73.0 (10.0) |
DEL PEAK 3(5Q31.2) WILD-TYPE | 161 | 101 | 0.0 - 94.1 (12.0) |
Figure S6. Get High-res Image Gene #9: 'del_5q31.2' versus Clinical Feature #1: 'Time to Death'

P value = 0.0108 (Wilcoxon-test), Q value = 0.19
Table S7. Gene #9: 'del_5q31.2' versus Clinical Feature #2: 'YEARS_TO_BIRTH'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
DEL PEAK 3(5Q31.2) MUTATED | 18 | 64.3 (13.0) |
DEL PEAK 3(5Q31.2) WILD-TYPE | 173 | 54.3 (16.1) |
Figure S7. Get High-res Image Gene #9: 'del_5q31.2' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

P value = 0.00127 (logrank test), Q value = 0.064
Table S8. Gene #14: 'del_12p13.2' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
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ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 10(12P13.2) MUTATED | 9 | 9 | 0.0 - 22.1 (7.0) |
DEL PEAK 10(12P13.2) WILD-TYPE | 169 | 107 | 0.0 - 94.1 (12.0) |
Figure S8. Get High-res Image Gene #14: 'del_12p13.2' versus Clinical Feature #1: 'Time to Death'

P value = 0.0103 (logrank test), Q value = 0.19
Table S9. Gene #18: 'del_17q11.2' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 14(17Q11.2) MUTATED | 12 | 11 | 0.0 - 49.0 (4.5) |
DEL PEAK 14(17Q11.2) WILD-TYPE | 166 | 105 | 0.0 - 94.1 (11.5) |
Figure S9. Get High-res Image Gene #18: 'del_17q11.2' versus Clinical Feature #1: 'Time to Death'

P value = 0.0199 (logrank test), Q value = 0.21
Table S10. Gene #19: 'del_18p11.21' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
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ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 15(18P11.21) MUTATED | 8 | 8 | 1.0 - 17.0 (9.5) |
DEL PEAK 15(18P11.21) WILD-TYPE | 170 | 108 | 0.0 - 94.1 (11.5) |
Figure S10. Get High-res Image Gene #19: 'del_18p11.21' versus Clinical Feature #1: 'Time to Death'

P value = 0.0114 (logrank test), Q value = 0.19
Table S11. Gene #20: 'del_20q13.13' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
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ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 16(20Q13.13) MUTATED | 4 | 4 | 0.0 - 10.0 (7.0) |
DEL PEAK 16(20Q13.13) WILD-TYPE | 174 | 112 | 0.0 - 94.1 (12.0) |
Figure S11. Get High-res Image Gene #20: 'del_20q13.13' versus Clinical Feature #1: 'Time to Death'

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Copy number data file = all_lesions.txt from GISTIC pipeline
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Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/LAML-TB/19782150/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LAML-TB/19775300/LAML-TB.merged_data.txt
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Number of patients = 191
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Number of significantly focal cnvs = 20
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Number of selected clinical features = 5
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Exclude genes that fewer than K tumors have mutations, 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 binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.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.