Correlation between gene methylation status and clinical features
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 19702 genes and 15 clinical features across 474 samples, statistically thresholded by Q value < 0.05, 14 clinical features related to at least one genes.

  • 6 genes correlated to 'Time to Death'.

    • FAM118B__1 ,  SYNGR3 ,  KLHL29 ,  SYN2__1 ,  ANKRD53 ,  ...

  • 345 genes correlated to 'AGE'.

    • MGA ,  NHLRC1 ,  INA ,  RANBP17 ,  C1ORF59 ,  ...

  • 280 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • OTOS ,  C1ORF91__1 ,  EIF3I__1 ,  ACTA1 ,  C10ORF137 ,  ...

  • 104 genes correlated to 'PATHOLOGY.T.STAGE'.

    • TBKBP1 ,  GJD3 ,  IFT140 ,  TMEM204 ,  PDGFB ,  ...

  • 1118 genes correlated to 'PATHOLOGY.N.STAGE'.

    • CPNE1__1 ,  RBM12__1 ,  PON2 ,  DAGLA ,  BMP1 ,  ...

  • 25 genes correlated to 'PATHOLOGY.M.STAGE'.

    • C1ORF91__1 ,  EIF3I__1 ,  LCA5 ,  CAPN5__1 ,  OMP ,  ...

  • 27 genes correlated to 'GENDER'.

    • ALG11__2 ,  UTP14C__1 ,  ETF1 ,  KIF4B ,  FAM35A ,  ...

  • 2303 genes correlated to 'HISTOLOGICAL.TYPE'.

    • PON2 ,  EMP1 ,  C8ORF73 ,  SLC6A12 ,  LAMP3 ,  ...

  • 45 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • SIK1 ,  SNX31 ,  STX17 ,  KIAA1143__1 ,  KIF15__1 ,  ...

  • 47 genes correlated to 'RADIATIONEXPOSURE'.

    • CHEK2 ,  HSCB ,  MGC21881 ,  CASP12 ,  TMEM63C ,  ...

  • 329 genes correlated to 'EXTRATHYROIDAL.EXTENSION'.

    • OTOS ,  DEFB131 ,  TBX19 ,  SLC16A3 ,  PA2G4P4 ,  ...

  • 7 genes correlated to 'COMPLETENESS.OF.RESECTION'.

    • ANKRD34B ,  CAPN5__1 ,  OMP ,  C17ORF108 ,  KCNJ14 ,  ...

  • 1004 genes correlated to 'NUMBER.OF.LYMPH.NODES'.

    • FUT2 ,  MET ,  TMEM173 ,  TAGLN2 ,  MACF1 ,  ...

  • 1 gene correlated to 'TUMOR.SIZE'.

    • TGFBR1

  • No genes correlated to 'MULTIFOCALITY'

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 genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test N=6 shorter survival N=4 longer survival N=2
AGE Spearman correlation test N=345 older N=343 younger N=2
NEOPLASM DISEASESTAGE ANOVA test N=280        
PATHOLOGY T STAGE Spearman correlation test N=104 higher stage N=59 lower stage N=45
PATHOLOGY N STAGE t test N=1118 class1 N=97 class0 N=1021
PATHOLOGY M STAGE ANOVA test N=25        
GENDER t test N=27 male N=13 female N=14
HISTOLOGICAL TYPE ANOVA test N=2303        
RADIATIONS RADIATION REGIMENINDICATION t test N=45 yes N=23 no N=22
RADIATIONEXPOSURE t test N=47 yes N=23 no N=24
EXTRATHYROIDAL EXTENSION ANOVA test N=329        
COMPLETENESS OF RESECTION ANOVA test N=7        
NUMBER OF LYMPH NODES Spearman correlation test N=1004 higher number.of.lymph.nodes N=20 lower number.of.lymph.nodes N=984
MULTIFOCALITY t test   N=0        
TUMOR SIZE Spearman correlation test N=1 higher tumor.size N=1 lower tumor.size N=0
Clinical variable #1: 'Time to Death'

6 genes related to 'Time to Death'.

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

Time to Death Duration (Months) 0-158.8 (median=14.1)
  censored N = 456
  death N = 13
     
  Significant markers N = 6
  associated with shorter survival 4
  associated with longer survival 2
List of 6 genes significantly associated with 'Time to Death' by Cox regression test

Table S2.  Get Full Table List of 6 genes significantly associated with 'Time to Death' by Cox regression test

HazardRatio Wald_P Q C_index
FAM118B__1 0 6.112e-07 0.012 0.229
SYNGR3 171 1.087e-06 0.021 0.743
KLHL29 0 1.403e-06 0.028 0.235
SYN2__1 331 1.634e-06 0.032 0.858
ANKRD53 391 2.382e-06 0.047 0.64
LOC150786 59001 2.531e-06 0.05 0.88

Figure S1.  Get High-res Image As an example, this figure shows the association of FAM118B__1 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 6.11e-07 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

345 genes related to 'AGE'.

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

AGE Mean (SD) 46.98 (16)
  Significant markers N = 345
  pos. correlated 343
  neg. correlated 2
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
MGA 0.5317 6.065e-36 1.19e-31
NHLRC1 0.494 1.576e-30 3.1e-26
INA 0.4853 2.27e-29 4.47e-25
RANBP17 0.4594 4.023e-26 7.93e-22
C1ORF59 0.4558 1.083e-25 2.13e-21
ACN9 0.4526 2.611e-25 5.14e-21
SYNGR3 0.4478 9.432e-25 1.86e-20
ZNF518B 0.4422 4.148e-24 8.17e-20
NTNG2 0.4242 3.968e-22 7.81e-18
OTUD7A 0.4242 4.004e-22 7.88e-18

Figure S2.  Get High-res Image As an example, this figure shows the association of MGA to 'AGE'. P value = 6.06e-36 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

280 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S5.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 271
  STAGE II 48
  STAGE III 106
  STAGE IV 2
  STAGE IVA 41
  STAGE IVC 4
     
  Significant markers N = 280
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S6.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
OTOS 7.576e-30 1.49e-25
C1ORF91__1 1.605e-29 3.16e-25
EIF3I__1 1.605e-29 3.16e-25
ACTA1 1.446e-26 2.85e-22
C10ORF137 6.644e-23 1.31e-18
LCA5 5.937e-22 1.17e-17
C2ORF34 4.26e-17 8.39e-13
PREPL 4.26e-17 8.39e-13
RABL2A 1.121e-15 2.21e-11
RPL23AP7 1.121e-15 2.21e-11

Figure S3.  Get High-res Image As an example, this figure shows the association of OTOS to 'NEOPLASM.DISEASESTAGE'. P value = 7.58e-30 with ANOVA analysis.

Clinical variable #4: 'PATHOLOGY.T.STAGE'

104 genes related to 'PATHOLOGY.T.STAGE'.

Table S7.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 2.12 (0.88)
  N
  1 138
  2 157
  3 158
  4 19
     
  Significant markers N = 104
  pos. correlated 59
  neg. correlated 45
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S8.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
TBKBP1 0.3038 1.564e-11 3.08e-07
GJD3 0.2934 7.97e-11 1.57e-06
IFT140 0.2928 8.698e-11 1.71e-06
TMEM204 0.2928 8.698e-11 1.71e-06
PDGFB 0.2836 3.506e-10 6.91e-06
CKMT2 0.2814 4.883e-10 9.62e-06
RNU5D__1 0.2814 4.883e-10 9.62e-06
RNU5E__1 0.2814 4.883e-10 9.62e-06
FLJ42875 0.2662 4.254e-09 8.38e-05
GGT7 0.263 6.603e-09 0.00013

Figure S4.  Get High-res Image As an example, this figure shows the association of TBKBP1 to 'PATHOLOGY.T.STAGE'. P value = 1.56e-11 with Spearman correlation analysis.

Clinical variable #5: 'PATHOLOGY.N.STAGE'

1118 genes related to 'PATHOLOGY.N.STAGE'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 213
  class1 214
     
  Significant markers N = 1118
  Higher in class1 97
  Higher in class0 1021
List of top 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S10.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.N.STAGE'

T(pos if higher in 'class1') ttestP Q AUC
CPNE1__1 -9.34 6.484e-19 1.28e-14 0.7313
RBM12__1 -9.34 6.484e-19 1.28e-14 0.7313
PON2 -9.34 7.331e-19 1.44e-14 0.7275
DAGLA -9.26 1.147e-18 2.26e-14 0.73
BMP1 -9.25 1.298e-18 2.56e-14 0.7277
MACF1 -9.25 1.501e-18 2.96e-14 0.7238
STARD5 -9.11 3.643e-18 7.18e-14 0.7286
XDH -8.97 1.276e-17 2.51e-13 0.716
SLC34A2 -8.93 1.341e-17 2.64e-13 0.7302
EPHA4 -8.92 1.966e-17 3.87e-13 0.7133

Figure S5.  Get High-res Image As an example, this figure shows the association of CPNE1__1 to 'PATHOLOGY.N.STAGE'. P value = 6.48e-19 with T-test analysis.

Clinical variable #6: 'PATHOLOGY.M.STAGE'

25 genes related to 'PATHOLOGY.M.STAGE'.

Table S11.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 258
  M1 7
  MX 208
     
  Significant markers N = 25
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S12.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
C1ORF91__1 4.859e-15 9.57e-11
EIF3I__1 4.859e-15 9.57e-11
LCA5 1.159e-13 2.28e-09
CAPN5__1 6.68e-10 1.32e-05
OMP 6.68e-10 1.32e-05
RPS10 2.882e-09 5.68e-05
PRPF31 1.29e-08 0.000254
TFPT 1.29e-08 0.000254
C2ORF34 2.591e-08 0.00051
PREPL 2.591e-08 0.00051

Figure S6.  Get High-res Image As an example, this figure shows the association of C1ORF91__1 to 'PATHOLOGY.M.STAGE'. P value = 4.86e-15 with ANOVA analysis.

Clinical variable #7: 'GENDER'

27 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 351
  MALE 123
     
  Significant markers N = 27
  Higher in MALE 13
  Higher in FEMALE 14
List of top 10 genes differentially expressed by 'GENDER'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
ALG11__2 41.78 1.331e-154 2.62e-150 0.9952
UTP14C__1 41.78 1.331e-154 2.62e-150 0.9952
ETF1 31.79 2.553e-79 5.03e-75 0.9879
KIF4B -17.82 4.254e-46 8.38e-42 0.9034
FAM35A -11.48 1.059e-25 2.09e-21 0.855
GLUD1__1 -11.48 1.059e-25 2.09e-21 0.855
WBP11P1 9.53 9.178e-18 1.81e-13 0.8038
ANKRD20A4 8.64 4.741e-16 9.34e-12 0.7426
CCDC121__1 7.07 1.817e-11 3.58e-07 0.7057
GPN1__1 7.07 1.817e-11 3.58e-07 0.7057

Figure S7.  Get High-res Image As an example, this figure shows the association of ALG11__2 to 'GENDER'. P value = 1.33e-154 with T-test analysis.

Clinical variable #8: 'HISTOLOGICAL.TYPE'

2303 genes related to 'HISTOLOGICAL.TYPE'.

Table S15.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  OTHER SPECIFY 9
  THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL 332
  THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) 98
  THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES) 35
     
  Significant markers N = 2303
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S16.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
PON2 2.343e-43 4.62e-39
EMP1 1.706e-42 3.36e-38
C8ORF73 2.415e-41 4.76e-37
SLC6A12 2.514e-41 4.95e-37
LAMP3 2.937e-41 5.79e-37
LEPR 5.396e-41 1.06e-36
LEPROT 5.396e-41 1.06e-36
LOC100126784 1.067e-39 2.1e-35
NAV2__1 1.067e-39 2.1e-35
C5ORF62 4.029e-39 7.93e-35

Figure S8.  Get High-res Image As an example, this figure shows the association of PON2 to 'HISTOLOGICAL.TYPE'. P value = 2.34e-43 with ANOVA analysis.

Clinical variable #9: 'RADIATIONS.RADIATION.REGIMENINDICATION'

45 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S17.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 14
  YES 460
     
  Significant markers N = 45
  Higher in YES 23
  Higher in NO 22
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S18.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
SIK1 9.54 3.426e-19 6.75e-15 0.6953
SNX31 8.26 3.369e-15 6.64e-11 0.7016
STX17 9.26 1.128e-13 2.22e-09 0.634
KIAA1143__1 8.9 2.543e-13 5.01e-09 0.7422
KIF15__1 8.9 2.543e-13 5.01e-09 0.7422
TAF7 7.78 3.849e-13 7.58e-09 0.7023
MYOM2 7.94 5.474e-12 1.08e-07 0.5366
HORMAD1 -8.56 3.131e-11 6.17e-07 0.7278
ZNHIT3 7.08 1.078e-10 2.12e-06 0.562
CBLN1 7.22 1.611e-10 3.17e-06 0.7325

Figure S9.  Get High-res Image As an example, this figure shows the association of SIK1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 3.43e-19 with T-test analysis.

Clinical variable #10: 'RADIATIONEXPOSURE'

47 genes related to 'RADIATIONEXPOSURE'.

Table S19.  Basic characteristics of clinical feature: 'RADIATIONEXPOSURE'

RADIATIONEXPOSURE Labels N
  NO 400
  YES 17
     
  Significant markers N = 47
  Higher in YES 23
  Higher in NO 24
List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

Table S20.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONEXPOSURE'

T(pos if higher in 'YES') ttestP Q AUC
CHEK2 -7.33 2.742e-12 5.4e-08 0.6022
HSCB -7.33 2.742e-12 5.4e-08 0.6022
MGC21881 -7.3 1.15e-11 2.27e-07 0.5853
CASP12 -7.61 3.384e-11 6.67e-07 0.6076
TMEM63C -7.47 5.819e-11 1.15e-06 0.6287
HESX1 7.19 1.291e-10 2.54e-06 0.6697
CYP3A4 7.36 4.623e-10 9.1e-06 0.666
POLR2F 7.34 5.845e-10 1.15e-05 0.6754
PHKB 6.54 7.862e-10 1.55e-05 0.7191
RAD54B 7.91 1.314e-09 2.59e-05 0.7494

Figure S10.  Get High-res Image As an example, this figure shows the association of CHEK2 to 'RADIATIONEXPOSURE'. P value = 2.74e-12 with T-test analysis.

Clinical variable #11: 'EXTRATHYROIDAL.EXTENSION'

329 genes related to 'EXTRATHYROIDAL.EXTENSION'.

Table S21.  Basic characteristics of clinical feature: 'EXTRATHYROIDAL.EXTENSION'

EXTRATHYROIDAL.EXTENSION Labels N
  MINIMAL (T3) 124
  MODERATE/ADVANCED (T4A) 15
  NONE 319
  VERY ADVANCED (T4B) 1
     
  Significant markers N = 329
List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

Table S22.  Get Full Table List of top 10 genes differentially expressed by 'EXTRATHYROIDAL.EXTENSION'

ANOVA_P Q
OTOS 2.782e-73 5.48e-69
DEFB131 3.473e-33 6.84e-29
TBX19 1.341e-23 2.64e-19
SLC16A3 4.797e-21 9.45e-17
PA2G4P4 3.558e-20 7.01e-16
BTBD12 4.612e-20 9.08e-16
C9ORF46 1.652e-17 3.25e-13
TRAM1L1 3.561e-17 7.01e-13
NPTN 4.155e-17 8.18e-13
ISL2 4.576e-17 9.01e-13

Figure S11.  Get High-res Image As an example, this figure shows the association of OTOS to 'EXTRATHYROIDAL.EXTENSION'. P value = 2.78e-73 with ANOVA analysis.

Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

7 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S23.  Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION Labels N
  R0 369
  R1 46
  R2 3
  RX 27
     
  Significant markers N = 7
List of 7 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S24.  Get Full Table List of 7 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

ANOVA_P Q
ANKRD34B 2.157e-19 4.25e-15
CAPN5__1 7.325e-18 1.44e-13
OMP 7.325e-18 1.44e-13
C17ORF108 7.62e-13 1.5e-08
KCNJ14 3.321e-09 6.54e-05
HPS3 2.336e-07 0.0046
FCRL1 1.411e-06 0.0278

Figure S12.  Get High-res Image As an example, this figure shows the association of ANKRD34B to 'COMPLETENESS.OF.RESECTION'. P value = 2.16e-19 with ANOVA analysis.

Clinical variable #13: 'NUMBER.OF.LYMPH.NODES'

1004 genes related to 'NUMBER.OF.LYMPH.NODES'.

Table S25.  Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES Mean (SD) 3.56 (6.2)
  Significant markers N = 1004
  pos. correlated 20
  neg. correlated 984
List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

Table S26.  Get Full Table List of top 10 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test

SpearmanCorr corrP Q
FUT2 -0.4279 2.66e-18 5.24e-14
MET -0.424 5.672e-18 1.12e-13
TMEM173 -0.4189 1.564e-17 3.08e-13
TAGLN2 -0.4152 3.179e-17 6.26e-13
MACF1 -0.413 4.829e-17 9.51e-13
CAPN2 -0.4102 8.153e-17 1.61e-12
STARD5 -0.4085 1.118e-16 2.2e-12
HDAC9 -0.405 2.163e-16 4.26e-12
CPNE1__1 -0.4049 2.192e-16 4.32e-12
RBM12__1 -0.4049 2.192e-16 4.32e-12

Figure S13.  Get High-res Image As an example, this figure shows the association of FUT2 to 'NUMBER.OF.LYMPH.NODES'. P value = 2.66e-18 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #14: 'MULTIFOCALITY'

No gene related to 'MULTIFOCALITY'.

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

MULTIFOCALITY Labels N
  MULTIFOCAL 214
  UNIFOCAL 250
     
  Significant markers N = 0
Clinical variable #15: 'TUMOR.SIZE'

One gene related to 'TUMOR.SIZE'.

Table S28.  Basic characteristics of clinical feature: 'TUMOR.SIZE'

TUMOR.SIZE Mean (SD) 2.94 (1.6)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

Table S29.  Get Full Table List of one gene significantly correlated to 'TUMOR.SIZE' by Spearman correlation test

SpearmanCorr corrP Q
TGFBR1 0.2396 2.308e-06 0.0455

Figure S14.  Get High-res Image As an example, this figure shows the association of TGFBR1 to 'TUMOR.SIZE'. P value = 2.31e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

  • Expresson data file = THCA-TP.meth.by_min_expr_corr.data.txt

  • Clinical data file = THCA-TP.clin.merged.picked.txt

  • Number of patients = 474

  • Number of genes = 19702

  • Number of clinical features = 15

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

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

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

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] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[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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