Correlation between miRseq expression and clinical features
Pancreatic Adenocarcinoma (Primary solid tumor)
23 May 2013 | analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1N877VG
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between miRseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1N877VG
Overview
Introduction

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

Summary

Testing the association between 515 genes and 8 clinical features across 20 samples, statistically thresholded by Q value < 0.05, no clinical feature related to at least one genes.

- No genes correlated to 'AGE', 'GENDER', 'HISTOLOGICAL.TYPE', 'DISTANT.METASTASIS', 'LYMPH.NODE.METASTASIS', 'COMPLETENESS.OF.RESECTION', 'NUMBER.OF.LYMPH.NODES', and 'NEOPLASM.DISEASESTAGE'.

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 |
--- | --- | --- | --- | --- | --- | ---
AGE | Spearman correlation test | N=0 |  |  |  |
GENDER | t test | N=0 |  |  |  |
HISTOLOGICAL TYPE | ANOVA test | N=0 |  |  |  |
DISTANT METASTASIS | ANOVA test | N=0 |  |  |  |
LYMPH NODE METASTASIS | t test | N=0 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=0 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |  |  |  |
NEOPLASM DISEASESTAGE | ANOVA test | N=0 |  |  |  |

Clinical variable #1: 'AGE'

No gene related to 'AGE'.

Table S1. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 66.35 (9.1)
| Significant markers | N = 0

Clinical variable #2: 'GENDER'

No gene related to 'GENDER'.

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

GENDER | Labels | N
| FEMALE | 10
| MALE | 10
| Significant markers | N = 0

Clinical variable #3: 'HISTOLOGICAL.TYPE'

No gene related to 'HISTOLOGICAL.TYPE'.

Table S3. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| PANCREAS-ADENOCARCINOMA DUCTAL TYPE | 17
| PANCREAS-ADENOCARCINOMA-OTHER SUBTYPE | 2
| PANCREAS-COLLOID (MUCINOUS NON-CYSTIC) CARCINOMA | 1
| Significant markers | N = 0

Clinical variable #4: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S4. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS | Labels | N
| M0 | 3
| M1 | 1
| MX | 16
| Significant markers | N = 0

Clinical variable #5: 'LYMPH.NODE.METASTASIS'

No gene related to 'LYMPH.NODE.METASTASIS'.

Table S5. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS | Labels | N
| N0 | 8
| N1 | 12
| Significant markers | N = 0

Clinical variable #6: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S6. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 13
| R1 | 5
| RX | 2
| Significant markers | N = 0

Clinical variable #7: 'NUMBER.OF.LYMPH.NODES'

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

Table S7. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 2.05 (2.9)
| Significant markers | N = 0

Clinical variable #8: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S8. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE IA | 2
| STAGE IB | 1
| STAGE IIA | 3
| STAGE IIB | 12
| STAGE III | 1
| STAGE IV | 1
| Significant markers | N = 0

Methods & Data
Input

- Expresson data file = PAAD-TP.miRseq_RPKM_log2.txt

- Clinical data file = PAAD-TP.clin.merged.picked.txt

- Number of patients = 20

- Number of genes = 515

- Number of clinical features = 8

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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] 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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