This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.
Testing the association between 2 variables and 14 clinical features across 678 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one variables.
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2 variables correlated to 'AGE'.
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MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT
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2 variables correlated to 'AGE_mutation.rate'.
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MUTATIONRATE_NONSYNONYMOUS , MUTATIONRATE_SILENT
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1 variable correlated to 'GENDER'.
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MUTATIONRATE_NONSYNONYMOUS
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2 variables correlated to 'HISTOLOGICAL_TYPE'.
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MUTATIONRATE_SILENT , MUTATIONRATE_NONSYNONYMOUS
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1 variable correlated to 'ETHNICITY'.
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MUTATIONRATE_NONSYNONYMOUS
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No variables correlated to 'DAYS_TO_DEATH_OR_LAST_FUP', 'NEOPLASM_DISEASESTAGE', 'PATHOLOGY_T_STAGE', 'PATHOLOGY_N_STAGE', 'PATHOLOGY_M_STAGE', 'KARNOFSKY_PERFORMANCE_SCORE', 'NUMBER_PACK_YEARS_SMOKED', 'YEAR_OF_TOBACCO_SMOKING_ONSET', and 'RACE'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant variables | Associated with | Associated with | ||
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DAYS_TO_DEATH_OR_LAST_FUP | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=2 | older | N=2 | younger | N=0 |
AGE | Linear Regression Analysis | N=2 | ||||
NEOPLASM_DISEASESTAGE | Kruskal-Wallis test | N=0 | ||||
PATHOLOGY_T_STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY_N_STAGE | Spearman correlation test | N=0 | ||||
PATHOLOGY_M_STAGE | Wilcoxon test | N=0 | ||||
GENDER | Wilcoxon test | N=1 | male | N=1 | female | N=0 |
KARNOFSKY_PERFORMANCE_SCORE | Spearman correlation test | N=0 | ||||
HISTOLOGICAL_TYPE | Kruskal-Wallis test | N=2 | ||||
NUMBER_PACK_YEARS_SMOKED | Spearman correlation test | N=0 | ||||
YEAR_OF_TOBACCO_SMOKING_ONSET | Spearman correlation test | N=0 | ||||
RACE | Kruskal-Wallis test | N=0 | ||||
ETHNICITY | Wilcoxon test | N=1 | not hispanic or latino | N=1 | hispanic or latino | N=0 |
No variable related to 'DAYS_TO_DEATH_OR_LAST_FUP'.
DAYS_TO_DEATH_OR_LAST_FUP | Duration (Months) | 0.1-194.8 (median=34.1) |
censored | N = 500 | |
death | N = 177 | |
Significant variables | N = 0 |
AGE | Mean (SD) | 59.58 (13) |
Significant variables | N = 2 | |
pos. correlated | 2 | |
neg. correlated | 0 |
AGE | Mean (SD) | 59.58 (13) |
Significant variables | N = 2 |
NEOPLASM_DISEASESTAGE | Labels | N |
STAGE I | 334 | |
STAGE II | 80 | |
STAGE III | 167 | |
STAGE IV | 86 | |
Significant variables | N = 0 |
PATHOLOGY_T_STAGE | Mean (SD) | 1.85 (0.94) |
N | ||
T1 | 347 | |
T2 | 98 | |
T3 | 223 | |
T4 | 10 | |
Significant variables | N = 0 |
PATHOLOGY_N_STAGE | Mean (SD) | 0.15 (0.41) |
N | ||
N0 | 275 | |
N1 | 36 | |
N2 | 6 | |
Significant variables | N = 0 |
PATHOLOGY_M_STAGE | Labels | N |
class0 | 478 | |
class1 | 78 | |
Significant variables | N = 0 |
GENDER | Labels | N |
FEMALE | 232 | |
MALE | 446 | |
Significant variables | N = 1 | |
Higher in MALE | 1 | |
Higher in FEMALE | 0 |
W(pos if higher in 'MALE') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
MUTATIONRATE_NONSYNONYMOUS | 56602.5 | 0.04432 | 0.0751 | 0.547 |
No variable related to 'KARNOFSKY_PERFORMANCE_SCORE'.
KARNOFSKY_PERFORMANCE_SCORE | Mean (SD) | 89.37 (17) |
Significant variables | N = 0 |
HISTOLOGICAL_TYPE | Labels | N |
KIDNEY CHROMOPHOBE | 66 | |
KIDNEY CLEAR CELL RENAL CARCINOMA | 451 | |
KIDNEY PAPILLARY RENAL CELL CARCINOMA | 161 | |
Significant variables | N = 2 |
No variable related to 'NUMBER_PACK_YEARS_SMOKED'.
NUMBER_PACK_YEARS_SMOKED | Mean (SD) | 30.51 (34) |
Significant variables | N = 0 |
No variable related to 'YEAR_OF_TOBACCO_SMOKING_ONSET'.
YEAR_OF_TOBACCO_SMOKING_ONSET | Mean (SD) | 1974.08 (15) |
Significant variables | N = 0 |
RACE | Labels | N |
AMERICAN INDIAN OR ALASKA NATIVE | 2 | |
ASIAN | 11 | |
BLACK OR AFRICAN AMERICAN | 66 | |
WHITE | 578 | |
Significant variables | N = 0 |
ETHNICITY | Labels | N |
HISPANIC OR LATINO | 32 | |
NOT HISPANIC OR LATINO | 444 | |
Significant variables | N = 1 | |
Higher in NOT HISPANIC OR LATINO | 1 | |
Higher in HISPANIC OR LATINO | 0 |
W(pos if higher in 'NOT HISPANIC OR LATINO') | wilcoxontestP | Q | AUC | |
---|---|---|---|---|
MUTATIONRATE_NONSYNONYMOUS | c("8645", "0.04038") | c("8645", "0.04038") | 0.0808 | 0.6085 |
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Expresson data file = KIPAN-TP.patients.counts_and_rates.txt
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Clinical data file = KIPAN-TP.merged_data.txt
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Number of patients = 678
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Number of variables = 2
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Number of clinical features = 14
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For clinical features selected for this analysis and their value conozzle.versions, please find a documentation on selected CDEs .
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Survival time data
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Survival time data is a combined value of days_to_death and days_to_last_followup. For each patient, it creates a combined value 'days_to_death_or_last_fup' using conversion process below.
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if 'vital_status'==1(dead), 'days_to_last_followup' is always NA. Thus, uses 'days_to_death' value for 'days_to_death_or_fup'
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if 'vital_status'==0(alive),
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if 'days_to_death'==NA & 'days_to_last_followup'!=NA, uses 'days_to_last_followup' value for 'days_to_death_or_fup'
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if 'days_to_death'!=NA, excludes this case in survival analysis and report the case.
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if 'vital_status'==NA,excludes this case in survival analysis and report the case.
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cf. In certain diesase types such as SKCM, days_to_death parameter is replaced with time_from_specimen_dx or time_from_specimen_procurement_to_death .
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This analysis excluded clinical variables that has only NA values.
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 groups (mutant or wild-type) of continuous type of clinical data, wilcoxon rank sum test (Mann and Whitney, 1947) was applied to compare their mean difference using 'wilcox.test(continuous.clinical ~ as.factor(group), exact=FALSE)' function in R. This test is equivalent to the Mann-Whitney test.
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.