(BRAF_Hotspot_Mutants cohort)
This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18144 genes and 7 clinical features across 67 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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2 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.
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KRTAP1-5|83895 , AGXT|189
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13 genes correlated to 'GENDER'.
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ZFY|7544 , USP9Y|8287 , CYORF15B|84663 , PRKY|5616 , RPS4Y1|6192 , ...
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9 genes correlated to 'DISTANT.METASTASIS'.
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PAX3|5077 , LOC728640|728640 , OCRL|4952 , ZNF546|339327 , USP9X|8239 , ...
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1 gene correlated to 'LYMPH.NODE.METASTASIS'.
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CABP7|164633
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No genes correlated to 'Time to Death', 'AGE', and 'NEOPLASM.DISEASESTAGE'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
---|---|---|---|---|---|---|
Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
PRIMARY SITE OF DISEASE | ANOVA test | N=2 | ||||
GENDER | t test | N=13 | male | N=11 | female | N=2 |
DISTANT METASTASIS | ANOVA test | N=9 | ||||
LYMPH NODE METASTASIS | ANOVA test | N=1 | ||||
NEOPLASM DISEASESTAGE | ANOVA test | N=0 |
Time to Death | Duration (Months) | 4.2-98.8 (median=15) |
censored | N = 17 | |
death | N = 19 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 50.27 (16) |
Significant markers | N = 0 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
DISTANT METASTASIS | 6 | |
PRIMARY TUMOR | 1 | |
REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) | 12 | |
REGIONAL LYMPH NODE | 48 | |
Significant markers | N = 2 |
ANOVA_P | Q | |
---|---|---|
KRTAP1-5|83895 | 5.656e-09 | 0.000103 |
AGXT|189 | 2.412e-06 | 0.0438 |
GENDER | Labels | N |
FEMALE | 22 | |
MALE | 45 | |
Significant markers | N = 13 | |
Higher in MALE | 11 | |
Higher in FEMALE | 2 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
ZFY|7544 | 20.79 | 4.412e-29 | 8e-25 | 1 |
USP9Y|8287 | 23.34 | 6.963e-24 | 1.26e-19 | 1 |
CYORF15B|84663 | 19.54 | 1.148e-23 | 2.08e-19 | 1 |
PRKY|5616 | 17.57 | 1.162e-21 | 2.11e-17 | 1 |
RPS4Y1|6192 | 20.34 | 5.237e-20 | 9.49e-16 | 1 |
XIST|7503 | -12.37 | 1.466e-17 | 2.66e-13 | 0.9607 |
KDM5D|8284 | 18.26 | 2.864e-11 | 5.19e-07 | 1 |
DDX3Y|8653 | 18.12 | 1.647e-10 | 2.99e-06 | 1 |
TTTY15|64595 | 18.13 | 2.752e-10 | 4.99e-06 | 1 |
TSIX|9383 | -8.33 | 3.626e-10 | 6.57e-06 | 0.9562 |
DISTANT.METASTASIS | Labels | N |
M0 | 56 | |
M1 | 1 | |
M1A | 1 | |
M1B | 1 | |
M1C | 2 | |
Significant markers | N = 9 |
ANOVA_P | Q | |
---|---|---|
PAX3|5077 | 2.127e-10 | 3.85e-06 |
LOC728640|728640 | 1.159e-08 | 0.00021 |
OCRL|4952 | 5.946e-08 | 0.00107 |
ZNF546|339327 | 1.109e-07 | 0.002 |
USP9X|8239 | 4.177e-07 | 0.00755 |
ZNHIT2|741 | 5.187e-07 | 0.00937 |
ZNF658|26149 | 5.291e-07 | 0.00956 |
NUDT12|83594 | 9.66e-07 | 0.0175 |
MAP3K13|9175 | 1.473e-06 | 0.0266 |
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 33 | |
N1 | 1 | |
N1A | 2 | |
N1B | 7 | |
N2A | 1 | |
N2B | 5 | |
N2C | 3 | |
N3 | 7 | |
NX | 2 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
CABP7|164633 | 1.634e-08 | 0.000296 |
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Expresson data file = SKCM-BRAF_Hotspot_Mutants.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = SKCM-BRAF_Hotspot_Mutants.clin.merged.picked.txt
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Number of patients = 67
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Number of genes = 18144
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Number of clinical features = 7
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 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 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 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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.