Correlation between mutation rate and clinical features
Overview
Introduction

This pipeline uses various statistical tests to identify selected clinical features related to mutation rate.

Summary

Testing the association between 2 variables and 39 clinical features across 38 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one variables.

  • 1 variable correlated to 'AGE_mutation.rate'.

    • MUTATIONRATE_NONSYNONYMOUS

  • 2 variables correlated to 'LOCATION_OF_POSITIVE_MARGINS'.

    • MUTATIONRATE_NONSYNONYMOUS ,  MUTATIONRATE_SILENT

  • No variables correlated to 'Time to Death', 'AGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'HISTOLOGICAL.TYPE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'NUMBER.OF.LYMPH.NODES', 'RACE', 'WEIGHT_KG_AT_DIAGNOSIS', 'TUMOR_STATUS', 'NEOPLASMHISTOLOGICGRADE', 'TOBACCO_SMOKING_YEAR_STOPPED', 'TOBACCO_SMOKING_PACK_YEARS_SMOKED', 'TOBACCO_SMOKING_HISTORY', 'PATIENT.AGEBEGANSMOKINGINYEARS', 'RADIATION_THERAPY_TYPE', 'PREGNANCIES_COUNT_TOTAL', 'PREGNANCIES_COUNT_STILLBIRTH', 'PATIENT.PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT', 'PREGNANCIES_COUNT_LIVE_BIRTH', 'PATIENT.PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT', 'PREGNANCIES_COUNT_ECTOPIC', 'LYMPH_NODE_LOCATION', 'MENOPAUSE_STATUS', 'LYMPHOVASCULAR_INVOLVEMENT', 'LYMPH_NODES_EXAMINED_HE_COUNT', 'LYMPH_NODES_EXAMINED', 'KERATINIZATION_SQUAMOUS_CELL', 'INITIAL_PATHOLOGIC_DX_YEAR', 'HISTORY_HORMONAL_CONTRACEPTIVES_USE', 'HEIGHT_CM_AT_DIAGNOSIS', 'CORPUS_INVOLVEMENT', 'CERVIX_SUV_RESULTS', 'AJCC_TUMOR_PATHOLOGIC_PT', and 'AGE_AT_DIAGNOSIS'.

Results
Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1.  Get Full Table This table shows the clinical features, statistical methods used, and the number of variables that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature Statistical test Significant variables Associated with                 Associated with
Time to Death Cox regression test   N=0        
AGE Spearman correlation test   N=0        
AGE Linear Regression Analysis N=1        
PATHOLOGY T STAGE Spearman correlation test   N=0        
PATHOLOGY N STAGE Wilcoxon test   N=0        
PATHOLOGY M STAGE Wilcoxon test   N=0        
HISTOLOGICAL TYPE Wilcoxon test   N=0        
RADIATIONS RADIATION REGIMENINDICATION Wilcoxon test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
NUMBER OF LYMPH NODES Spearman correlation test   N=0        
RACE Kruskal-Wallis test   N=0        
WEIGHT_KG_AT_DIAGNOSIS Spearman correlation test   N=0        
TUMOR_STATUS Wilcoxon test   N=0        
NEOPLASMHISTOLOGICGRADE Kruskal-Wallis test   N=0        
TOBACCO_SMOKING_YEAR_STOPPED Spearman correlation test   N=0        
TOBACCO_SMOKING_PACK_YEARS_SMOKED Spearman correlation test   N=0        
TOBACCO_SMOKING_HISTORY Kruskal-Wallis test   N=0        
PATIENT AGEBEGANSMOKINGINYEARS Spearman correlation test   N=0        
RADIATION_THERAPY_TYPE Kruskal-Wallis test   N=0        
PREGNANCIES_COUNT_TOTAL Spearman correlation test   N=0        
PREGNANCIES_COUNT_STILLBIRTH Spearman correlation test   N=0        
PATIENT PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT Spearman correlation test   N=0        
PREGNANCIES_COUNT_LIVE_BIRTH Spearman correlation test   N=0        
PATIENT PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT Spearman correlation test   N=0        
PREGNANCIES_COUNT_ECTOPIC Wilcoxon test   N=0        
LYMPH_NODE_LOCATION Kruskal-Wallis test   N=0        
LOCATION_OF_POSITIVE_MARGINS Kruskal-Wallis test N=2        
MENOPAUSE_STATUS Kruskal-Wallis test   N=0        
LYMPHOVASCULAR_INVOLVEMENT Wilcoxon test   N=0        
LYMPH_NODES_EXAMINED_HE_COUNT Spearman correlation test   N=0        
LYMPH_NODES_EXAMINED Spearman correlation test   N=0        
KERATINIZATION_SQUAMOUS_CELL Wilcoxon test   N=0        
INITIAL_PATHOLOGIC_DX_YEAR Spearman correlation test   N=0        
HISTORY_HORMONAL_CONTRACEPTIVES_USE Wilcoxon test   N=0        
HEIGHT_CM_AT_DIAGNOSIS Spearman correlation test   N=0        
CORPUS_INVOLVEMENT Wilcoxon test   N=0        
CERVIX_SUV_RESULTS Spearman correlation test   N=0        
AJCC_TUMOR_PATHOLOGIC_PT Kruskal-Wallis test   N=0        
AGE_AT_DIAGNOSIS Spearman correlation test   N=0        
Clinical variable #1: 'Time to Death'

No variable related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.5-177 (median=36.7)
  censored N = 24
  death N = 14
     
  Significant variables N = 0
Clinical variable #2: 'AGE'

No variable related to 'AGE'.

Table S2.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 46.95 (14)
  Significant variables N = 0
Clinical variable #3: 'AGE'

One variable related to 'AGE'.

Table S3.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 46.95 (14)
  Significant variables N = 1
List of one variable associated with 'AGE'

Table S4.  Get Full Table List of one variable significantly correlated to 'AGE' by Linear regression analysis [lm (mutation rate ~ age)]. Compared to a correlation analysis testing for interdependence of the variables, a regression model attempts to describe the dependence of a variable on one (or more) explanatory variables assuming that there is a one-way causal effect from the explanatory variable(s) to the response variable. If 'Residuals vs Fitted' plot (a standard residual plot) shows a random pattern indicating a good fit for a linear model, it explains linear regression relationship between Mutation rate and age factor. Adj.R-squared (= Explained variation / Total variation) indicates regression model's explanatory power.

Adj.R.squared F P Residual.std.err DF coef(intercept) coef.p(intercept)
MUTATIONRATE_NONSYNONYMOUS 0.0789 4.17 0.0485 6.95e-06 36 1.7e-07 ( -2.59e-06 ) 0.0485 ( 0.529 )
Clinical variable #4: 'PATHOLOGY.T.STAGE'

No variable related to 'PATHOLOGY.T.STAGE'.

Table S5.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.26 (0.51)
  N
  1 24
  2 6
  3 1
     
  Significant variables N = 0
Clinical variable #5: 'PATHOLOGY.N.STAGE'

No variable related to 'PATHOLOGY.N.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 17
  class1 15
     
  Significant variables N = 0
Clinical variable #6: 'PATHOLOGY.M.STAGE'

No variable related to 'PATHOLOGY.M.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 19
  MX 13
     
  Significant variables N = 0
Clinical variable #7: 'HISTOLOGICAL.TYPE'

No variable related to 'HISTOLOGICAL.TYPE'.

Table S8.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  CERVICAL SQUAMOUS CELL CARCINOMA 35
  ENDOCERVICAL TYPE OF ADENOCARCINOMA 3
     
  Significant variables N = 0
Clinical variable #8: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No variable related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S9.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 22
  YES 16
     
  Significant variables N = 0
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No variable related to 'NUMBERPACKYEARSSMOKED'.

Table S10.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 18.43 (8)
  Significant variables N = 0
Clinical variable #10: 'NUMBER.OF.LYMPH.NODES'

No variable related to 'NUMBER.OF.LYMPH.NODES'.

Table S11.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 1.42 (3)
  Significant variables N = 0
Clinical variable #11: 'RACE'

No variable related to 'RACE'.

Table S12.  Basic characteristics of clinical feature: 'RACE'

RACE Labels N
  ASIAN 1
  BLACK OR AFRICAN AMERICAN 5
  WHITE 32
     
  Significant variables N = 0
Clinical variable #12: 'WEIGHT_KG_AT_DIAGNOSIS'

No variable related to 'WEIGHT_KG_AT_DIAGNOSIS'.

Table S13.  Basic characteristics of clinical feature: 'WEIGHT_KG_AT_DIAGNOSIS'

WEIGHT_KG_AT_DIAGNOSIS Mean (SD) 70.29 (14)
  Significant variables N = 0
Clinical variable #13: 'TUMOR_STATUS'

No variable related to 'TUMOR_STATUS'.

Table S14.  Basic characteristics of clinical feature: 'TUMOR_STATUS'

TUMOR_STATUS Labels N
  TUMOR FREE 22
  WITH TUMOR 10
     
  Significant variables N = 0
Clinical variable #14: 'NEOPLASMHISTOLOGICGRADE'

No variable related to 'NEOPLASMHISTOLOGICGRADE'.

Table S15.  Basic characteristics of clinical feature: 'NEOPLASMHISTOLOGICGRADE'

NEOPLASMHISTOLOGICGRADE Labels N
  G1 2
  G2 19
  G3 17
     
  Significant variables N = 0
Clinical variable #15: 'TOBACCO_SMOKING_YEAR_STOPPED'

No variable related to 'TOBACCO_SMOKING_YEAR_STOPPED'.

Table S16.  Basic characteristics of clinical feature: 'TOBACCO_SMOKING_YEAR_STOPPED'

TOBACCO_SMOKING_YEAR_STOPPED Mean (SD) 1996.83 (5.7)
  Value N
  1988 1
  1995 2
  1997 1
  2003 2
     
  Significant variables N = 0
Clinical variable #16: 'TOBACCO_SMOKING_PACK_YEARS_SMOKED'

No variable related to 'TOBACCO_SMOKING_PACK_YEARS_SMOKED'.

Table S17.  Basic characteristics of clinical feature: 'TOBACCO_SMOKING_PACK_YEARS_SMOKED'

TOBACCO_SMOKING_PACK_YEARS_SMOKED Mean (SD) 18.43 (8)
  Significant variables N = 0
Clinical variable #17: 'TOBACCO_SMOKING_HISTORY'

No variable related to 'TOBACCO_SMOKING_HISTORY'.

Table S18.  Basic characteristics of clinical feature: 'TOBACCO_SMOKING_HISTORY'

TOBACCO_SMOKING_HISTORY Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 9
  CURRENT REFORMED SMOKER FOR > 15 YEARS 2
  CURRENT SMOKER 9
  LIFELONG NON-SMOKER 17
     
  Significant variables N = 0
Clinical variable #18: 'PATIENT.AGEBEGANSMOKINGINYEARS'

No variable related to 'PATIENT.AGEBEGANSMOKINGINYEARS'.

Table S19.  Basic characteristics of clinical feature: 'PATIENT.AGEBEGANSMOKINGINYEARS'

PATIENT.AGEBEGANSMOKINGINYEARS Mean (SD) 20.45 (6.2)
  Significant variables N = 0
Clinical variable #19: 'RADIATION_THERAPY_TYPE'

No variable related to 'RADIATION_THERAPY_TYPE'.

Table S20.  Basic characteristics of clinical feature: 'RADIATION_THERAPY_TYPE'

RADIATION_THERAPY_TYPE Labels N
  COMBINATION 15
  EXTERNAL 1
  EXTERNAL BEAM 8
     
  Significant variables N = 0
Clinical variable #20: 'PREGNANCIES_COUNT_TOTAL'

No variable related to 'PREGNANCIES_COUNT_TOTAL'.

Table S21.  Basic characteristics of clinical feature: 'PREGNANCIES_COUNT_TOTAL'

PREGNANCIES_COUNT_TOTAL Mean (SD) 3.14 (1.9)
  Significant variables N = 0
Clinical variable #21: 'PREGNANCIES_COUNT_STILLBIRTH'

No variable related to 'PREGNANCIES_COUNT_STILLBIRTH'.

Table S22.  Basic characteristics of clinical feature: 'PREGNANCIES_COUNT_STILLBIRTH'

PREGNANCIES_COUNT_STILLBIRTH Mean (SD) 0.16 (0.58)
  Value N
  0 28
  1 2
  3 1
     
  Significant variables N = 0
Clinical variable #22: 'PATIENT.PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT'

No variable related to 'PATIENT.PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT'.

Table S23.  Basic characteristics of clinical feature: 'PATIENT.PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT'

PATIENT.PATIENTPREGNANCYSPONTANEOUSABORTIONCOUNT Mean (SD) 0.33 (0.65)
  Value N
  0 25
  1 5
  2 3
     
  Significant variables N = 0
Clinical variable #23: 'PREGNANCIES_COUNT_LIVE_BIRTH'

No variable related to 'PREGNANCIES_COUNT_LIVE_BIRTH'.

Table S24.  Basic characteristics of clinical feature: 'PREGNANCIES_COUNT_LIVE_BIRTH'

PREGNANCIES_COUNT_LIVE_BIRTH Mean (SD) 2.08 (1.3)
  Value N
  0 5
  1 7
  2 13
  3 4
  4 8
     
  Significant variables N = 0
Clinical variable #24: 'PATIENT.PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT'

No variable related to 'PATIENT.PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT'.

Table S25.  Basic characteristics of clinical feature: 'PATIENT.PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT'

PATIENT.PATIENTPREGNANCYTHERAPEUTICABORTIONCOUNT Mean (SD) 0.68 (1)
  Value N
  0 20
  1 4
  2 4
  3 3
     
  Significant variables N = 0
Clinical variable #25: 'PREGNANCIES_COUNT_ECTOPIC'

No variable related to 'PREGNANCIES_COUNT_ECTOPIC'.

Table S26.  Basic characteristics of clinical feature: 'PREGNANCIES_COUNT_ECTOPIC'

PREGNANCIES_COUNT_ECTOPIC Labels N
  class0 27
  class1 4
     
  Significant variables N = 0
Clinical variable #26: 'LYMPH_NODE_LOCATION'

No variable related to 'LYMPH_NODE_LOCATION'.

Table S27.  Basic characteristics of clinical feature: 'LYMPH_NODE_LOCATION'

LYMPH_NODE_LOCATION Labels N
  2003 1
  2010 1
  COMMON ILIAC 1
  PELVIC (EXTERNAL ILIAC, INTERNAL ILIAC, OBTURATOR) 12
     
  Significant variables N = 0
Clinical variable #27: 'LOCATION_OF_POSITIVE_MARGINS'

2 variables related to 'LOCATION_OF_POSITIVE_MARGINS'.

Table S28.  Basic characteristics of clinical feature: 'LOCATION_OF_POSITIVE_MARGINS'

LOCATION_OF_POSITIVE_MARGINS Labels N
  MICROSCOPIC PARAMETRIAL INVOLVEMENT 4
  OTHER LOCATION, SPECIFY 7
  POSITIVE VAGINAL MARGIN 2
     
  Significant variables N = 2
List of 2 variables associated with 'LOCATION_OF_POSITIVE_MARGINS'

Table S29.  Get Full Table List of 2 variables differentially expressed by 'LOCATION_OF_POSITIVE_MARGINS'

ANOVA_P Q
MUTATIONRATE_NONSYNONYMOUS 0.02069 0.0388
MUTATIONRATE_SILENT 0.01941 0.0388
Clinical variable #28: 'MENOPAUSE_STATUS'

No variable related to 'MENOPAUSE_STATUS'.

Table S30.  Basic characteristics of clinical feature: 'MENOPAUSE_STATUS'

MENOPAUSE_STATUS Labels N
  INDETERMINATE (NEITHER PRE OR POSTMENOPAUSAL) 2
  PERI (6-12 MONTHS SINCE LAST MENSTRUAL PERIOD) 1
  POST (PRIOR BILATERAL OVARIECTOMY OR >12 MO SINCE LMP WITH NO PRIOR HYSTERECTOMY) 13
  PRE (<6 MONTHS SINCE LMP AND NO PRIOR BILATERAL OVARIECTOMY AND NOT ON ESTROGEN REPLACEMENT) 19
     
  Significant variables N = 0
Clinical variable #29: 'LYMPHOVASCULAR_INVOLVEMENT'

No variable related to 'LYMPHOVASCULAR_INVOLVEMENT'.

Table S31.  Basic characteristics of clinical feature: 'LYMPHOVASCULAR_INVOLVEMENT'

LYMPHOVASCULAR_INVOLVEMENT Labels N
  ABSENT 9
  PRESENT 21
     
  Significant variables N = 0
Clinical variable #30: 'LYMPH_NODES_EXAMINED_HE_COUNT'

No variable related to 'LYMPH_NODES_EXAMINED_HE_COUNT'.

Table S32.  Basic characteristics of clinical feature: 'LYMPH_NODES_EXAMINED_HE_COUNT'

LYMPH_NODES_EXAMINED_HE_COUNT Mean (SD) 1.42 (3)
  Significant variables N = 0
Clinical variable #31: 'LYMPH_NODES_EXAMINED'

No variable related to 'LYMPH_NODES_EXAMINED'.

Table S33.  Basic characteristics of clinical feature: 'LYMPH_NODES_EXAMINED'

LYMPH_NODES_EXAMINED Mean (SD) 24.87 (14)
  Significant variables N = 0
Clinical variable #32: 'KERATINIZATION_SQUAMOUS_CELL'

No variable related to 'KERATINIZATION_SQUAMOUS_CELL'.

Table S34.  Basic characteristics of clinical feature: 'KERATINIZATION_SQUAMOUS_CELL'

KERATINIZATION_SQUAMOUS_CELL Labels N
  KERATINIZING SQUAMOUS CELL CARCINOMA 12
  NON-KERATINIZING SQUAMOUS CELL CARCINOMA 14
     
  Significant variables N = 0
Clinical variable #33: 'INITIAL_PATHOLOGIC_DX_YEAR'

No variable related to 'INITIAL_PATHOLOGIC_DX_YEAR'.

Table S35.  Basic characteristics of clinical feature: 'INITIAL_PATHOLOGIC_DX_YEAR'

INITIAL_PATHOLOGIC_DX_YEAR Mean (SD) 2003.13 (5)
  Significant variables N = 0
Clinical variable #34: 'HISTORY_HORMONAL_CONTRACEPTIVES_USE'

No variable related to 'HISTORY_HORMONAL_CONTRACEPTIVES_USE'.

Table S36.  Basic characteristics of clinical feature: 'HISTORY_HORMONAL_CONTRACEPTIVES_USE'

HISTORY_HORMONAL_CONTRACEPTIVES_USE Labels N
  FORMER USER 9
  NEVER USED 10
     
  Significant variables N = 0
Clinical variable #35: 'HEIGHT_CM_AT_DIAGNOSIS'

No variable related to 'HEIGHT_CM_AT_DIAGNOSIS'.

Table S37.  Basic characteristics of clinical feature: 'HEIGHT_CM_AT_DIAGNOSIS'

HEIGHT_CM_AT_DIAGNOSIS Mean (SD) 162 (7.3)
  Significant variables N = 0
Clinical variable #36: 'CORPUS_INVOLVEMENT'

No variable related to 'CORPUS_INVOLVEMENT'.

Table S38.  Basic characteristics of clinical feature: 'CORPUS_INVOLVEMENT'

CORPUS_INVOLVEMENT Labels N
  ABSENT 21
  PRESENT 6
     
  Significant variables N = 0
Clinical variable #37: 'CERVIX_SUV_RESULTS'

No variable related to 'CERVIX_SUV_RESULTS'.

Table S39.  Basic characteristics of clinical feature: 'CERVIX_SUV_RESULTS'

CERVIX_SUV_RESULTS Mean (SD) 13.23 (4.5)
  Value N
  8.7 1
  9.95 1
  16.92 1
  17.36 1
     
  Significant variables N = 0
Clinical variable #38: 'AJCC_TUMOR_PATHOLOGIC_PT'

No variable related to 'AJCC_TUMOR_PATHOLOGIC_PT'.

Table S40.  Basic characteristics of clinical feature: 'AJCC_TUMOR_PATHOLOGIC_PT'

AJCC_TUMOR_PATHOLOGIC_PT Labels N
  T1B 9
  T1B1 12
  T1B2 3
  T2 1
  T2A1 1
  T2B 4
  T3B 1
  TX 1
     
  Significant variables N = 0
Clinical variable #39: 'AGE_AT_DIAGNOSIS'

No variable related to 'AGE_AT_DIAGNOSIS'.

Table S41.  Basic characteristics of clinical feature: 'AGE_AT_DIAGNOSIS'

AGE_AT_DIAGNOSIS Mean (SD) 46.95 (14)
  Significant variables N = 0
Methods & Data
Input

  • Expresson data file = CESC-TP.patients.counts_and_rates.txt

  • Clinical data file = CESC-TP.merged_data.txt

  • Number of patients = 38

  • Number of variables = 2

  • Number of clinical features = 39

Survival analysis

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

Correlation analysis

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

Student's t-test analysis

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

ANOVA analysis

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

Q value calculation

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.

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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