This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.
Testing the association between copy number variation 16 focal events and 5 clinical features across 191 patients, 10 significant findings detected with Q value < 0.25.
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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'.
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 (0.152) |
0.0236 (0.189) |
0.0922 (0.405) |
0.389 (0.741) |
1 (1.00) |
del 5q31 2 | 18 (9%) | 173 |
0.0179 (0.177) |
0.0108 (0.152) |
0.0464 (0.286) |
1 (1.00) |
1 (1.00) |
amp 11q23 3 | 17 (9%) | 174 |
0.137 (0.477) |
0.0171 (0.177) |
0.45 (0.8) |
1 (1.00) |
0.249 (0.63) |
del 3p13 | 8 (4%) | 183 |
0.000606 (0.0484) |
0.112 (0.446) |
0.295 (0.703) |
0.0962 (0.405) |
1 (1.00) |
del 12p13 2 | 10 (5%) | 181 |
0.00127 (0.0509) |
0.367 (0.734) |
0.351 (0.734) |
1 (1.00) |
1 (1.00) |
del 17q11 2 | 13 (7%) | 178 |
0.0103 (0.152) |
0.321 (0.733) |
0.775 (1.00) |
0.651 (0.969) |
1 (1.00) |
del 18p11 21 | 9 (5%) | 182 |
0.0199 (0.177) |
0.427 (0.777) |
0.185 (0.56) |
0.555 (0.894) |
1 (1.00) |
del 20q13 13 | 4 (2%) | 187 |
0.0114 (0.152) |
0.0674 (0.317) |
0.627 (0.965) |
0.299 (0.703) |
1 (1.00) |
amp 1p33 | 7 (4%) | 184 |
0.202 (0.578) |
0.119 (0.455) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
amp 20q11 21 | 3 (2%) | 188 |
0.184 (0.56) |
0.346 (0.734) |
0.252 (0.63) |
0.236 (0.63) |
1 (1.00) |
del 7p12 1 | 16 (8%) | 175 |
0.166 (0.552) |
0.484 (0.842) |
0.604 (0.948) |
1 (1.00) |
1 (1.00) |
del 7q32 3 | 23 (12%) | 168 |
0.0445 (0.286) |
0.189 (0.56) |
0.656 (0.969) |
0.757 (1.00) |
1 (1.00) |
del 9q21 32 | 5 (3%) | 186 |
0.735 (1.00) |
0.417 (0.776) |
0.378 (0.738) |
0.36 (0.734) |
1 (1.00) |
del 12q21 33 | 3 (2%) | 188 |
0.367 (0.734) |
0.0366 (0.266) |
0.252 (0.63) |
1 (1.00) |
1 (1.00) |
del 16q23 1 | 9 (5%) | 182 |
0.0671 (0.317) |
0.518 (0.864) |
0.513 (0.864) |
0.559 (0.894) |
1 (1.00) |
del 17p13 2 | 15 (8%) | 176 |
0.0528 (0.301) |
0.129 (0.469) |
0.0565 (0.301) |
0.666 (0.969) |
1 (1.00) |
P value = 0.0171 (Wilcoxon-test), Q value = 0.18
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
AMP PEAK 2(11Q23.3) MUTATED | 17 | 63.3 (12.1) |
AMP PEAK 2(11Q23.3) WILD-TYPE | 174 | 54.4 (16.2) |
P value = 0.00622 (logrank test), Q value = 0.15
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
AMP PEAK 4(21Q22.2) MUTATED | 12 | 10 | 1.0 - 24.0 (5.5) |
AMP PEAK 4(21Q22.2) WILD-TYPE | 166 | 106 | 0.0 - 94.1 (12.0) |
P value = 0.0236 (Wilcoxon-test), Q value = 0.19
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
AMP PEAK 4(21Q22.2) MUTATED | 14 | 63.7 (16.7) |
AMP PEAK 4(21Q22.2) WILD-TYPE | 177 | 54.6 (15.9) |
P value = 0.000606 (logrank test), Q value = 0.048
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 1(3P13) MUTATED | 8 | 7 | 0.0 - 14.0 (1.5) |
DEL PEAK 1(3P13) WILD-TYPE | 170 | 109 | 0.0 - 94.1 (12.0) |
P value = 0.0179 (logrank test), Q value = 0.18
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 2(5Q31.2) MUTATED | 17 | 15 | 1.0 - 73.0 (10.0) |
DEL PEAK 2(5Q31.2) WILD-TYPE | 161 | 101 | 0.0 - 94.1 (12.0) |
P value = 0.0108 (Wilcoxon-test), Q value = 0.15
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 191 | 55.2 (16.1) |
DEL PEAK 2(5Q31.2) MUTATED | 18 | 64.3 (13.0) |
DEL PEAK 2(5Q31.2) WILD-TYPE | 173 | 54.3 (16.1) |
P value = 0.00127 (logrank test), Q value = 0.051
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 6(12P13.2) MUTATED | 9 | 9 | 0.0 - 22.1 (7.0) |
DEL PEAK 6(12P13.2) WILD-TYPE | 169 | 107 | 0.0 - 94.1 (12.0) |
P value = 0.0103 (logrank test), Q value = 0.15
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 10(17Q11.2) MUTATED | 12 | 11 | 0.0 - 49.0 (4.5) |
DEL PEAK 10(17Q11.2) WILD-TYPE | 166 | 105 | 0.0 - 94.1 (11.5) |
P value = 0.0199 (logrank test), Q value = 0.18
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 11(18P11.21) MUTATED | 8 | 8 | 1.0 - 17.0 (9.5) |
DEL PEAK 11(18P11.21) WILD-TYPE | 170 | 108 | 0.0 - 94.1 (11.5) |
P value = 0.0114 (logrank test), Q value = 0.15
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 178 | 116 | 0.0 - 94.1 (11.0) |
DEL PEAK 12(20Q13.13) MUTATED | 4 | 4 | 0.0 - 10.0 (7.0) |
DEL PEAK 12(20Q13.13) WILD-TYPE | 174 | 112 | 0.0 - 94.1 (12.0) |
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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/22529563/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LAML-TB/22506504/LAML-TB.merged_data.txt
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Number of patients = 191
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Number of significantly focal cnvs = 16
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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.
In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.