This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.
Testing the association between 17814 genes and 5 clinical features across 529 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.
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2 genes correlated to 'Time to Death'.
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RPS26 , PPP1R14D
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386 genes correlated to 'AGE'.
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ESR1 , CNTNAP3 , FOXD2 , KLK6 , NUDT16 , ...
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6 genes correlated to 'GENDER'.
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PI3 , TMEM16C , CACNG1 , RP13-36C9.6 , MAPK4 , ...
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3 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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OR13C4 , TMEM92 , CYP3A5
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12 genes correlated to 'NEOADJUVANT.THERAPY'.
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ZCCHC7 , DUSP1 , MGC33407 , RGS1 , C2ORF60 , ...
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=2 | shorter survival | N=2 | longer survival | N=0 |
AGE | Spearman correlation test | N=386 | older | N=188 | younger | N=198 |
GENDER | t test | N=6 | male | N=1 | female | N=5 |
RADIATIONS RADIATION REGIMENINDICATION | t test | N=3 | yes | N=3 | no | N=0 |
NEOADJUVANT THERAPY | t test | N=12 | yes | N=5 | no | N=7 |
Time to Death | Duration (Months) | 0.1-223.4 (median=24.1) |
censored | N = 432 | |
death | N = 65 | |
Significant markers | N = 2 | |
associated with shorter survival | 2 | |
associated with longer survival | 0 |
AGE | Mean (SD) | 57.89 (13) |
Significant markers | N = 386 | |
pos. correlated | 188 | |
neg. correlated | 198 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
ESR1 | 0.414 | 2.515e-23 | 4.48e-19 |
CNTNAP3 | -0.2907 | 9.302e-12 | 1.66e-07 |
FOXD2 | 0.289 | 1.233e-11 | 2.2e-07 |
KLK6 | -0.2889 | 1.247e-11 | 2.22e-07 |
NUDT16 | 0.2875 | 1.591e-11 | 2.83e-07 |
MAGED4B | -0.2858 | 2.117e-11 | 3.77e-07 |
KRT17 | -0.2842 | 2.751e-11 | 4.9e-07 |
MFGE8 | -0.2842 | 2.763e-11 | 4.92e-07 |
SYT8 | -0.2838 | 2.942e-11 | 5.24e-07 |
PHOSPHO2 | 0.2791 | 6.34e-11 | 1.13e-06 |
GENDER | Labels | N |
FEMALE | 523 | |
MALE | 6 | |
Significant markers | N = 6 | |
Higher in MALE | 1 | |
Higher in FEMALE | 5 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
PI3 | -9.33 | 2.686e-11 | 4.79e-07 | 0.7129 |
TMEM16C | -14.29 | 1.571e-10 | 2.8e-06 | 0.9261 |
CACNG1 | 18.46 | 1.712e-08 | 0.000305 | 0.9614 |
RP13-36C9.6 | -6.29 | 6.462e-07 | 0.0115 | 0.6651 |
MAPK4 | -9.13 | 1.424e-06 | 0.0254 | 0.8011 |
PLA2G3 | -10.66 | 1.754e-06 | 0.0312 | 0.8311 |
3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 147 | |
YES | 382 | |
Significant markers | N = 3 | |
Higher in YES | 3 | |
Higher in NO | 0 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
OR13C4 | 5.11 | 6.374e-07 | 0.0114 | 0.63 |
TMEM92 | 4.98 | 9.615e-07 | 0.0171 | 0.6099 |
CYP3A5 | 4.96 | 1.028e-06 | 0.0183 | 0.5852 |
NEOADJUVANT.THERAPY | Labels | N |
NO | 221 | |
YES | 308 | |
Significant markers | N = 12 | |
Higher in YES | 5 | |
Higher in NO | 7 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
ZCCHC7 | -5.7 | 2.181e-08 | 0.000388 | 0.639 |
DUSP1 | -5.32 | 1.584e-07 | 0.00282 | 0.6308 |
MGC33407 | 5.31 | 1.786e-07 | 0.00318 | 0.6328 |
RGS1 | -5.25 | 2.221e-07 | 0.00396 | 0.6173 |
C2ORF60 | 5.15 | 3.791e-07 | 0.00675 | 0.6169 |
EGR1 | -5.12 | 4.448e-07 | 0.00792 | 0.6247 |
OR13C4 | 5.02 | 7.424e-07 | 0.0132 | 0.62 |
FOS | -5.02 | 7.445e-07 | 0.0133 | 0.6208 |
EED | 4.93 | 1.093e-06 | 0.0195 | 0.6048 |
NLRP12 | 4.84 | 1.701e-06 | 0.0303 | 0.5973 |
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Expresson data file = BRCA.medianexp.txt
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Clinical data file = BRCA.clin.merged.picked.txt
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Number of patients = 529
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Number of genes = 17814
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Number of clinical features = 5
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-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. Location of data archives could not be determined.