LUAD/00: Correlation between gene mutation status and clinical
Overview
Introduction

This pipeline checks the correlation between mutation status of genes recurrently mutated in current cancer type to selected clinical features.

Summary

Testing the association between mutation status of 27 genes and 6 clinical features across 44 samples, no significant finding detected with P value <= 0.05 and Q value <= 0.25.

  • No gene mutations related to clinical features.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association results between 27 gene mutations and 6 clinical features. Shown in the table are P values (Q values). Thresholded by P value <= 0.05 and Q value <= 0.25, no significant finding detected.

Clinical
Features 		Time
to
Death 		AGE HISTOLOGICAL
TYPE 		GENDER PATHOLOGY
T 		PATHOLOGY
N
nMutated nWild-Type survival continuous binary binary multiclass(3) multiclass(3)
ABCB5 5 39 0.352
(1.00) 		0.227
(1.00) 		0.744
(1.00) 		0.197
(1.00) 		0.572
(1.00)
ADAMTS12 8 36 0.65
(1.00) 		0.851
(1.00) 		0.971
(1.00) 		0.569
(1.00) 		0.771
(1.00)
CSMD1 9 35 0.0855
(1.00) 		0.178
(1.00) 		0.734
(1.00) 		0.223
(1.00) 		0.52
(1.00) 		0.07
(1.00)
CSMD3 11 33 0.218
(1.00) 		0.0534
(1.00) 		0.854
(1.00) 		0.861
(1.00) 		0.724
(1.00) 		0.216
(1.00)
FRAS1 6 38 0.766
(1.00) 		0.958
(1.00) 		0.674
(1.00) 		0.42
(1.00) 		0.522
(1.00) 		0.572
(1.00)
GPR112 8 36 0.869
(1.00) 		0.851
(1.00) 		0.971
(1.00) 		0.692
(1.00) 		0.101
(1.00)
KEAP1 5 39 0.386
(1.00) 		0.838
(1.00) 		0.527
(1.00) 		0.197
(1.00) 		0.0718
(1.00)
LAMA2 5 39 0.2
(1.00) 		0.838
(1.00) 		0.744
(1.00) 		0.522
(1.00) 		0.983
(1.00)
LRP1B 13 31 0.721
(1.00) 		0.996
(1.00) 		0.457
(1.00) 		0.94
(1.00) 		0.105
(1.00) 		0.215
(1.00)
MUC16 20 24 0.796
(1.00) 		0.789
(1.00) 		0.839
(1.00) 		0.934
(1.00) 		0.113
(1.00) 		0.625
(1.00)
NOTCH4 6 38 0.199
(1.00) 		0.674
(1.00) 		0.936
(1.00) 		0.172
(1.00) 		0.759
(1.00)
PAPPA2 6 38 0.186
(1.00) 		0.674
(1.00) 		0.936
(1.00) 		0.127
(1.00) 		0.278
(1.00)
RYR2 11 33 0.66
(1.00) 		0.472
(1.00) 		0.199
(1.00) 		0.861
(1.00) 		0.0995
(1.00) 		0.499
(1.00)
TTN 15 29 0.895
(1.00) 		0.359
(1.00) 		0.279
(1.00) 		0.53
(1.00) 		0.592
(1.00) 		0.246
(1.00)
USH2A 5 39 0.355
(1.00) 		0.838
(1.00) 		0.527
(1.00) 		0.103
(1.00) 		0.399
(1.00)
PCDH15 7 37 0.998
(1.00) 		0.921
(1.00) 		0.664
(1.00) 		0.19
(1.00) 		0.338
(1.00)
CACNA1E 9 35 0.513
(1.00) 		0.896
(1.00) 		0.654
(1.00) 		0.296
(1.00) 		0.55
(1.00) 		0.655
(1.00)
MYH13 5 39 0.422
(1.00) 		0.838
(1.00) 		0.744
(1.00)
FLG 7 37 0.697
(1.00) 		0.921
(1.00) 		0.205
(1.00) 		0.34
(1.00) 		0.278
(1.00)
OBSCN 5 39 0.357
(1.00) 		0.838
(1.00) 		0.744
(1.00) 		0.522
(1.00)
CNGB3 5 39 0.41
(1.00) 		0.456
(1.00) 		0.838
(1.00) 		0.744
(1.00) 		0.582
(1.00) 		0.348
(1.00)
FBN2 8 36 0.194
(1.00) 		0.336
(1.00) 		0.851
(1.00) 		0.409
(1.00) 		0.569
(1.00) 		0.928
(1.00)
OVCH1 5 39 0.357
(1.00) 		0.838
(1.00) 		0.744
(1.00) 		0.187
(1.00)
MYH2 5 39 0.754
(1.00) 		0.227
(1.00) 		0.527
(1.00)
RELN 5 39 0.501
(1.00) 		0.838
(1.00) 		0.744
(1.00) 		0.477
(1.00) 		0.108
(1.00)
SPTA1 7 37 0.871
(1.00) 		0.101
(1.00) 		0.664
(1.00) 		0.823
(1.00) 		0.338
(1.00)
LAMA1 5 39 0.17
(1.00) 		0.425
(1.00) 		0.527
(1.00) 		0.187
(1.00) 		0.399
(1.00)
Methods & Data
Input

Input Data

  • Cluster data file = LUAD.mutsig.cluster.txt

  • Clinical data file = LUAD.clin.merged.picked.txt

  • Number of samples = 44

  • Number of clustering variables = 27

  • Number of filtered clinical features = 6

  • Minimum size criteria to remove small clusters = 5