Correlation between mRNAseq expression and clinical features
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1NP232R
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1NP232R
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 18274 genes and 9 clinical features across 503 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 25 genes correlated to 'AGE'.

    • RANBP17|64901 ,  WFDC1|58189 ,  RFPL1S|10740 ,  UTY|7404 ,  NEFH|4744 ,  ...

  • 1620 genes correlated to 'NEOPLASM.DISEASESTAGE'.

    • PLEKHA9|51054 ,  NR3C2|4306 ,  IL20RB|53833 ,  INHBE|83729 ,  UBE2C|11065 ,  ...

  • 2075 genes correlated to 'PATHOLOGY.T.STAGE'.

    • NR3C2|4306 ,  ZNF132|7691 ,  PLEKHA9|51054 ,  FKBP11|51303 ,  FAM122A|116224 ,  ...

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

    • C11ORF34|349633 ,  PITX2|5308 ,  ATP6V1D|51382 ,  HEMGN|55363 ,  C9ORF135|138255 ,  ...

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

    • INHBE|83729 ,  IL20RB|53833 ,  IGF2BP3|10643 ,  CEP55|55165 ,  CENPA|1058 ,  ...

  • 249 genes correlated to 'GENDER'.

    • XIST|7503 ,  PRKY|5616 ,  NLGN4Y|22829 ,  RPS4Y1|6192 ,  ZFY|7544 ,  ...

  • No genes correlated to 'Time to Death', 'KARNOFSKY.PERFORMANCE.SCORE', and 'NUMBERPACKYEARSSMOKED'.

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=0        
AGE Spearman correlation test N=25 older N=5 younger N=20
NEOPLASM DISEASESTAGE ANOVA test N=1620        
PATHOLOGY T STAGE Spearman correlation test N=2075 higher stage N=1114 lower stage N=961
PATHOLOGY N STAGE t test N=6 class1 N=1 class0 N=5
PATHOLOGY M STAGE ANOVA test N=246        
GENDER t test N=249 male N=152 female N=97
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

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

Time to Death Duration (Months) 0.1-120.6 (median=37.1)
  censored N = 336
  death N = 166
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

25 genes related to 'AGE'.

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

AGE Mean (SD) 60.63 (12)
  Significant markers N = 25
  pos. correlated 5
  neg. correlated 20
List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3.  Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

SpearmanCorr corrP Q
RANBP17|64901 -0.2742 4.143e-10 7.57e-06
WFDC1|58189 -0.2634 2.051e-09 3.75e-05
RFPL1S|10740 -0.262 3.272e-09 5.98e-05
UTY|7404 -0.2814 2.284e-08 0.000417
NEFH|4744 -0.2448 2.77e-08 0.000506
PALLD|23022 -0.2405 4.905e-08 0.000896
DIO2|1734 -0.2294 2.089e-07 0.00382
ZFY|7544 -0.2435 2.914e-07 0.00532
MAPKAPK2|9261 0.2236 4.152e-07 0.00758
NKAPL|222698 -0.221 5.851e-07 0.0107

Figure S1.  Get High-res Image As an example, this figure shows the association of RANBP17|64901 to 'AGE'. P value = 4.14e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

1620 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S4.  Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE Labels N
  STAGE I 244
  STAGE II 55
  STAGE III 124
  STAGE IV 80
     
  Significant markers N = 1620
List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S5.  Get Full Table List of top 10 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

ANOVA_P Q
PLEKHA9|51054 1.229e-17 2.25e-13
NR3C2|4306 2.259e-17 4.13e-13
IL20RB|53833 1.045e-16 1.91e-12
INHBE|83729 1.705e-16 3.11e-12
UBE2C|11065 1.813e-16 3.31e-12
ACADSB|36 3.975e-16 7.26e-12
FKBP11|51303 4.998e-16 9.13e-12
ALDH6A1|4329 7.821e-16 1.43e-11
CEP55|55165 7.914e-16 1.45e-11
PITX1|5307 1.111e-15 2.03e-11

Figure S2.  Get High-res Image As an example, this figure shows the association of PLEKHA9|51054 to 'NEOPLASM.DISEASESTAGE'. P value = 1.23e-17 with ANOVA analysis.

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

2075 genes related to 'PATHOLOGY.T.STAGE'.

Table S6.  Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'

PATHOLOGY.T.STAGE Mean (SD) 1.9 (0.96)
  N
  1 250
  2 66
  3 176
  4 11
     
  Significant markers N = 2075
  pos. correlated 1114
  neg. correlated 961
List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

Table S7.  Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T.STAGE' by Spearman correlation test

SpearmanCorr corrP Q
NR3C2|4306 -0.3775 1.743e-18 3.18e-14
ZNF132|7691 -0.3668 1.842e-17 3.37e-13
PLEKHA9|51054 0.3662 2.063e-17 3.77e-13
FKBP11|51303 0.3577 1.26e-16 2.3e-12
FAM122A|116224 -0.3494 6.849e-16 1.25e-11
TSPAN7|7102 -0.3484 8.385e-16 1.53e-11
TMEM150C|441027 -0.348 9.164e-16 1.67e-11
ANKRD56|345079 -0.3467 1.265e-15 2.31e-11
NOP2|4839 0.3434 2.29e-15 4.18e-11
EMCN|51705 -0.343 2.471e-15 4.51e-11

Figure S3.  Get High-res Image As an example, this figure shows the association of NR3C2|4306 to 'PATHOLOGY.T.STAGE'. P value = 1.74e-18 with Spearman correlation analysis.

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

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

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'

PATHOLOGY.N.STAGE Labels N
  class0 235
  class1 17
     
  Significant markers N = 6
  Higher in class1 1
  Higher in class0 5
List of 6 genes differentially expressed by 'PATHOLOGY.N.STAGE'

Table S9.  Get Full Table List of 6 genes differentially expressed by 'PATHOLOGY.N.STAGE'

T(pos if higher in 'class1') ttestP Q AUC
C11ORF34|349633 -7.74 4.659e-09 8.51e-05 0.7156
PITX2|5308 7.03 1.642e-07 0.003 0.7876
ATP6V1D|51382 -6.24 3.198e-07 0.00584 0.7524
HEMGN|55363 -6.07 4.583e-07 0.00837 0.7464
C9ORF135|138255 -5.49 1.412e-06 0.0258 0.6743
AHSP|51327 -5.96 1.892e-06 0.0345 0.7577

Figure S4.  Get High-res Image As an example, this figure shows the association of C11ORF34|349633 to 'PATHOLOGY.N.STAGE'. P value = 4.66e-09 with T-test analysis.

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

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

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'

PATHOLOGY.M.STAGE Labels N
  M0 421
  M1 79
  MX 3
     
  Significant markers N = 246
List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGY.M.STAGE'

ANOVA_P Q
INHBE|83729 1.459e-11 2.67e-07
IL20RB|53833 1.543e-11 2.82e-07
IGF2BP3|10643 3.884e-11 7.1e-07
CEP55|55165 7.579e-11 1.38e-06
CENPA|1058 1.269e-10 2.32e-06
GTSE1|51512 2.508e-10 4.58e-06
BIRC5|332 2.998e-10 5.48e-06
UBE2C|11065 3.878e-10 7.08e-06
CCNB2|9133 4.443e-10 8.12e-06
PLEKHA9|51054 5.139e-10 9.39e-06

Figure S5.  Get High-res Image As an example, this figure shows the association of INHBE|83729 to 'PATHOLOGY.M.STAGE'. P value = 1.46e-11 with ANOVA analysis.

Clinical variable #7: 'GENDER'

249 genes related to 'GENDER'.

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

GENDER Labels N
  FEMALE 172
  MALE 331
     
  Significant markers N = 249
  Higher in MALE 152
  Higher in FEMALE 97
List of top 10 genes differentially expressed by 'GENDER'

Table S13.  Get Full Table List of top 10 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
XIST|7503 -45.29 1.933e-171 3.53e-167 0.9848
PRKY|5616 40.59 1.679e-112 3.07e-108 0.986
NLGN4Y|22829 39.04 3.117e-87 5.7e-83 0.9854
RPS4Y1|6192 37.63 2.99e-77 5.46e-73 0.9897
ZFY|7544 38.5 1.934e-72 3.53e-68 0.9873
TSIX|9383 -23.98 2.149e-71 3.93e-67 0.9653
DDX3Y|8653 32.71 1.193e-60 2.18e-56 0.9823
KDM5C|8242 -17.37 1.159e-51 2.12e-47 0.9004
NCRNA00183|554203 -16.65 5.062e-47 9.25e-43 0.8661
KDM5D|8284 26.94 3.374e-42 6.16e-38 0.9806

Figure S6.  Get High-res Image As an example, this figure shows the association of XIST|7503 to 'GENDER'. P value = 1.93e-171 with T-test analysis.

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S14.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 90.86 (18)
  Score N
  0 1
  70 1
  80 3
  90 13
  100 17
     
  Significant markers N = 0
Clinical variable #9: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

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

NUMBERPACKYEARSSMOKED Mean (SD) 33.2 (14)
  Value N
  10 1
  30 1
  40 2
  46 1
     
  Significant markers N = 0
Methods & Data
Input

  • Expresson data file = KIRC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

  • Number of patients = 503

  • Number of genes = 18274

  • Number of clinical features = 9

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.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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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