(primary solid tumor cohort)
This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 18258 genes and 9 clinical features across 36 samples, statistically thresholded by Q value < 0.05, 1 clinical feature related to at least one genes.
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17 genes correlated to 'HISTOLOGICAL.TYPE'.
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MST4|51765 , MTERF|7978 , SGSM3|27352 , ZNF673|55634 , MUL1|79594 , ...
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No genes correlated to 'Time to Death', 'AGE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'TOBACCOSMOKINGHISTORYINDICATOR', 'DISTANT.METASTASIS', 'LYMPH.NODE.METASTASIS', and 'NUMBER.OF.LYMPH.NODES'.
Complete statistical result table is provided in Supplement Table 1
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
HISTOLOGICAL TYPE | ANOVA test | N=17 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 | ||||
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 | ||||
TOBACCOSMOKINGHISTORYINDICATOR | Spearman correlation test | N=0 | ||||
DISTANT METASTASIS | t test | N=0 | ||||
LYMPH NODE METASTASIS | t test | N=0 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 0.1-177 (median=6) |
censored | N = 28 | |
death | N = 7 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 47.58 (12) |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
CERVICAL SQUAMOUS CELL CARCINOMA | 31 | |
ENDOCERVICAL TYPE OF ADENOCARCINOMA | 1 | |
SQUAMOUS CELL CARCINOMA | 4 | |
Significant markers | N = 17 |
ANOVA_P | Q | |
---|---|---|
MST4|51765 | 1.062e-11 | 1.93e-07 |
MTERF|7978 | 6.414e-11 | 1.17e-06 |
SGSM3|27352 | 9.901e-10 | 1.8e-05 |
ZNF673|55634 | 1.961e-09 | 3.57e-05 |
MUL1|79594 | 2.092e-09 | 3.81e-05 |
HOXA7|3204 | 6.264e-09 | 0.000114 |
ANKS4B|257629 | 1.441e-08 | 0.000262 |
TBX10|347853 | 1.772e-08 | 0.000322 |
MYBBP1A|10514 | 2.802e-08 | 0.00051 |
USP10|9100 | 1.179e-07 | 0.00214 |
No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 13 | |
YES | 23 | |
Significant markers | N = 0 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 18.8 (11) |
Significant markers | N = 0 |
No gene related to 'TOBACCOSMOKINGHISTORYINDICATOR'.
TOBACCOSMOKINGHISTORYINDICATOR | Mean (SD) | 1.91 (1.1) |
Value | N | |
1 | 16 | |
2 | 10 | |
3 | 1 | |
4 | 6 | |
Significant markers | N = 0 |
DISTANT.METASTASIS | Labels | N |
M0 | 23 | |
MX | 8 | |
Significant markers | N = 0 |
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 20 | |
N1 | 12 | |
Significant markers | N = 0 |
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Expresson data file = CESC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt
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Clinical data file = CESC-TP.clin.merged.picked.txt
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Number of patients = 36
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Number of genes = 18258
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Number of clinical features = 9
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.