We developed DOSE (Yu et al. 2015 ) package to promote the investigation of diseases. DOSE provides five methods for measuring semantic similarities among DO terms and gene products , hypergeometric model and gene set enrichment analysis (GSEA) for associating disease with gene list and extracting disease association insight from genome wide expression profiles.
Disease over-representation analysis
DOSE supports enrichment analysis of Disease Ontology (DO) (Schriml et al. 2011 ) , Network of Cancer Gene (A. et al. 2016 ) and Disease Gene Network (DisGeNET) (Janet et al. 2015 ) . In addition, several visualization methods were provided by enrichplot to help interpreting semantic and enrichment results.
Over-representation analysis for disease ontology
In the following example, we selected fold change above 1.5 as the differential genes and analyzing their disease association.
[1] "4312" "8318" "10874" "55143" "55388" "991"
x <- enrichDO ( gene = gene , ont = "HDO" ,
pvalueCutoff = 0.05 ,
pAdjustMethod = "BH" ,
universe = names ( geneList ) ,
minGSSize = 5 ,
maxGSSize = 500 ,
qvalueCutoff = 0.05 ,
readable = FALSE )
head ( x )
ID Description GeneRatio BgRatio RichFactor
DOID:0060306 DOID:0060306 Meier-Gorlin syndrome 6/273 10/6078 0.6000000
DOID:10534 DOID:10534 stomach cancer 25/273 205/6078 0.1219512
DOID:5041 DOID:5041 esophageal cancer 18/273 132/6078 0.1363636
DOID:820 DOID:820 myocarditis 8/273 31/6078 0.2580645
DOID:1107 DOID:1107 esophageal carcinoma 16/273 117/6078 0.1367521
DOID:1612 DOID:1612 breast cancer 35/273 398/6078 0.0879397
FoldEnrichment zScore pvalue p.adjust qvalue
DOID:0060306 13.358242 8.481228 1.402836e-06 0.001273775 0.001058772
DOID:10534 2.715090 5.416997 4.109986e-06 0.001865933 0.001550979
DOID:5041 3.035964 5.128253 2.117499e-05 0.006408964 0.005327182
DOID:820 5.745480 5.744019 4.782074e-05 0.009274126 0.007708728
DOID:1107 3.044614 4.842498 5.908904e-05 0.009274126 0.007708728
DOID:1612 1.957866 4.286443 8.098096e-05 0.009274126 0.007708728
geneID
DOID:0060306 8318/81620/4174/990/23594/4998
DOID:10534 4312/2305/10403/259266/8140/81930/332/2146/8061/4318/3576/8792/6352/4288/3131/2952/347902/3572/563/7031/6926/3117/2018/2066/3169
DOID:5041 4312/3868/8140/7850/2146/4321/2921/4318/3576/6890/2952/563/7373/771/2018/2066/3169/11122
DOID:820 6280/6279/3627/29851/8792/1493/2697/4982
DOID:1107 4312/3868/8140/2146/4321/4318/3576/6890/2952/563/7373/771/2018/2066/3169/11122
DOID:1612 4312/6241/983/2146/3887/6790/891/23532/3161/993/5347/55215/55723/875/8438/9700/5888/7083/898/1493/6352/4288/3551/185/2952/367/1634/4582/3479/9370/3117/652/4137/3169/10551
Count
DOID:0060306 6
DOID:10534 25
DOID:5041 18
DOID:820 8
DOID:1107 16
DOID:1612 35
The enrichDO() session 16.1 if you need to conver other gene ID types to entrezgene ID.
The ont parameter can be “HDO” (Human Disease Ontology), “HPO” (Human Phenotype Ontology) or “MPO” (Mouse Phenotype Ontology). pvalueCutoff setting the cutoff value of p value and adjusted p value; pAdjustMethod setting the p value correction methods, include the Bonferroni correction (“bonferroni”), Holm (“holm”), Hochberg (“hochberg”), Hommel (“hommel”), Benjamini & Hochberg (“BH”) and Benjamini & Yekutieli (“BY”) while qvalueCutoff is used to control q -values.
The universe setting the background gene universe for testing. If user do not explicitly setting this parameter, enrichDO()
The minGSSize (and maxGSSize) indicates that only those DO terms that have more than minGSSize (and less than maxGSSize) genes annotated will be tested.
The readable is a logical parameter, indicates whether the entrezgene IDs will mapping to gene symbols or not (see also setReadable ).
Over-representation analysis for the network of cancer gene
Network of Cancer Gene (NCG) (A. et al. 2016 ) is a manually curated repository of cancer genes. NCG release 5.0 (Aug. 2015) collects 1,571 cancer genes from 175 published studies. DOSE supports analyzing gene list and determine whether they are enriched in genes known to be mutated in a given cancer type.
ID
pan-cancer_paediatric pan-cancer_paediatric
triple_negative_breast_cancer triple_negative_breast_cancer
bladder_cancer bladder_cancer
pancreatic_cancer_(all_histologies) pancreatic_cancer_(all_histologies)
soft_tissue_sarcoma soft_tissue_sarcoma
paediatric_high-grade_glioma paediatric_high-grade_glioma
Description
pan-cancer_paediatric pan-cancer_paediatric
triple_negative_breast_cancer triple_negative_breast_cancer
bladder_cancer bladder_cancer
pancreatic_cancer_(all_histologies) pancreatic_cancer_(all_histologies)
soft_tissue_sarcoma soft_tissue_sarcoma
paediatric_high-grade_glioma paediatric_high-grade_glioma
GeneRatio BgRatio RichFactor
pan-cancer_paediatric 162/2281 183/3177 0.8852459
triple_negative_breast_cancer 71/2281 75/3177 0.9466667
bladder_cancer 97/2281 112/3177 0.8660714
pancreatic_cancer_(all_histologies) 40/2281 42/3177 0.9523810
soft_tissue_sarcoma 26/2281 26/3177 1.0000000
paediatric_high-grade_glioma 25/2281 25/3177 1.0000000
FoldEnrichment zScore pvalue
pan-cancer_paediatric 1.232979 5.179242 1.833773e-08
triple_negative_breast_cancer 1.318527 4.453534 4.290660e-07
bladder_cancer 1.206273 3.545563 1.253690e-04
pancreatic_cancer_(all_histologies) 1.326486 3.397967 1.262162e-04
soft_tissue_sarcoma 1.392810 3.208441 1.742793e-04
paediatric_high-grade_glioma 1.392810 3.145636 2.434966e-04
p.adjust qvalue
pan-cancer_paediatric 1.613721e-06 7.721152e-07
triple_negative_breast_cancer 1.887890e-05 9.032967e-06
bladder_cancer 2.776757e-03 1.328592e-03
pancreatic_cancer_(all_histologies) 2.776757e-03 1.328592e-03
soft_tissue_sarcoma 3.067315e-03 1.467615e-03
paediatric_high-grade_glioma 3.073768e-03 1.470702e-03
geneID
pan-cancer_paediatric 2146/55353/4609/1029/3575/22806/3418/3066/2120/30012/867/7468/7545/3195/865/64109/4613/613/11177/7490/238/10736/10054/5771/4893/140885/1785/9760/3417/6597/6476/9126/4869/10320/7307/80204/1050/10992/8028/2312/6608/896/894/2196/4849/7023/5093/5079/5293/5727/55181/171017/51322/5781/3718/55294/60/673/8085/5897/4851/1665/51176/1108/7764/10664/6098/2332/2201/6495/3845/7015/1441/2782/64919/4298/23512/8239/29102/6929/8021/6134/6598/4209/5290/22941/8726/207/3717/2033/10716/4928/6932/694/5156/10019/6886/9968/7080/2623/7874/1654/4149/3020/23219/55252/55729/10735/5728/4853/23451/51341/387/3206/6146/79718/2624/63035/3815/171023/23269/25/23592/5896/7403/2260/54880/3716/9203/57178/6777/5789/4297/29072/90/546/120/25836/8289/4345/9611/5925/4763/1997/1499/7157/3399/5295/1387/4602/51564/1027/4005/2322/2078/678/6403/55709/1277/7494/64061/2625
triple_negative_breast_cancer 6790/898/4609/1029/1789/4436/2120/867/7128/1788/1030/7490/2271/238/675/2047/4914/1316/5291/5293/5781/55294/8085/4851/4170/3845/355/1616/4854/5290/207/2033/4233/29110/2903/5979/5728/4853/2624/3815/10000/7403/2260/55193/472/5789/4297/2065/4286/8626/8405/8289/10499/55164/5925/4763/23405/1499/4921/7157/5295/1387/2078/324/7248/7048/22894/3480/2045/2066/2625
bladder_cancer 9700/57211/2175/9603/1029/11168/2072/8997/79949/54663/688/6882/4893/8454/6693/56288/2195/10992/1026/64783/896/677/26038/6256/55294/60/8085/4851/841/3265/7175/1999/730051/3845/23484/7015/8243/10605/8295/4854/5290/51043/2033/4780/23224/23217/2064/23385/55252/10735/8241/10672/5728/4853/23451/374291/387/7799/171023/288/30849/4152/9794/7403/287/57634/463/472/4297/2065/2262/3280/23232/8289/9611/5925/2068/56339/4763/7157/2186/1387/3910/7536/2261/7248/23037/6709/54961/23345/57125/7832/79633/10628/22906/388/3169
pancreatic_cancer_(all_histologies) 1029/4771/8997/7159/2011/6597/7307/10992/3710/6710/55294/7091/3845/23654/7046/3096/4089/91/8241/54549/92/23451/63035/7403/55193/23309/472/800/29072/23077/23499/8289/54894/6416/7157/4088/182/7048/2199/26960
soft_tissue_sarcoma 999/6850/4914/4342/2185/55294/2041/4851/2044/4058/5290/4486/5297/5728/3815/2324/7403/546/5925/4763/1499/7157/5159/2045/3667/2066
paediatric_high-grade_glioma 4609/1029/1019/4613/1030/1956/4914/896/894/673/8493/5290/4233/5156/1021/63035/54880/4916/90/546/4763/7157/5295/595/4915
Count
pan-cancer_paediatric 162
triple_negative_breast_cancer 71
bladder_cancer 97
pancreatic_cancer_(all_histologies) 40
soft_tissue_sarcoma 26
paediatric_high-grade_glioma 25
Over-representation analysis for the disease gene network
DisGeNET (Janet et al. 2015 ) is an integrative and comprehensive resources of gene-disease associations from several public data sources and the literature. It contains gene-disease associations and snp-gene-disease associations.
The enrichment analysis of disease-gene associations is supported by the enrichDGN function and analysis of snp-gene-disease associations is supported by the enrichDGNv function.
ID Description GeneRatio BgRatio
C0010278 C0010278 Craniosynostosis 43/497 488/21671
C0853879 C0853879 Invasive carcinoma of breast 42/497 473/21671
C4733092 C4733092 estrogen receptor-negative breast cancer 34/497 356/21671
C3642347 C3642347 Basal-Like Breast Carcinoma 28/497 245/21671
C3642345 C3642345 Luminal A Breast Carcinoma 22/497 153/21671
C0036202 C0036202 Sarcoidosis 36/497 413/21671
RichFactor FoldEnrichment zScore pvalue p.adjust
C0010278 0.08811475 3.842122 9.728932 4.609534e-14 2.267976e-10
C0853879 0.08879493 3.871780 9.674768 7.105190e-14 2.267976e-10
C4733092 0.09550562 4.164391 9.223137 2.446675e-12 4.864593e-09
C3642347 0.11428571 4.983271 9.606353 3.047991e-12 4.864593e-09
C3642345 0.14379085 6.269802 10.021789 7.034749e-12 8.438458e-09
C0036202 0.08716707 3.800800 8.804448 7.930882e-12 8.438458e-09
qvalue
C0010278 1.636811e-10
C0853879 1.636811e-10
C4733092 3.510804e-09
C3642347 3.510804e-09
C3642345 6.090082e-09
C0036202 6.090082e-09
geneID
C0010278 4312/8318/6280/1062/6279/6278/3627/820/27299/6362/81620/2146/3002/29968/990/4318/4069/3576/6890/23594/26279/1493/6352/4998/2152/2697/185/4330/5327/4982/1300/3667/2200/9607/3572/563/7031/3479/6424/1846/3117/1308/2625
C0853879 4312/7153/6278/9787/9582/51203/890/983/5080/2146/1111/9232/10855/4171/6664/4102/2173/4318/701/3576/1978/8836/53335/1894/7980/8792/8842/2151/185/2952/367/4982/4582/6926/3479/1602/23158/2066/3169/5304/2625/5241
C4733092 2305/6278/79733/6241/81930/81620/2146/3620/29968/11004/8061/3576/1894/2491/7083/8792/214/5327/367/4982/3667/4582/27324/3479/1846/80129/4137/8839/3169/1408/5304/2625/5241/10551
C3642347 2305/1062/4605/9833/7368/11065/10232/55765/5163/2146/2568/3620/6790/6664/29127/2173/4318/3576/3159/8792/6663/27324/3479/1846/18/3169/2625/5241
C3642345 2305/9833/7153/55355/1111/3161/4318/3576/2001/6663/4288/2152/185/4128/4582/27324/80129/3169/5304/8614/2625/5241
C0036202 4312/6280/6279/10403/3627/6373/4283/27299/6362/3002/4321/6355/6364/29851/4318/5004/4069/3576/26227/6890/6352/4485/23541/185/7043/6863/2952/4982/25802/4582/2053/3479/3117/2167/80736/1524
Count
C0010278 43
C0853879 42
C4733092 34
C3642347 28
C3642345 22
C0036202 36
snp <- c ( "rs1401296" , "rs9315050" , "rs5498" , "rs1524668" , "rs147377392" , "rs841" , "rs909253" , "rs7193343" , "rs3918232" , "rs3760396" ,
"rs2231137" , "rs10947803" , "rs17222919" , "rs386602276" , "rs11053646" ,
"rs1805192" , "rs139564723" , "rs2230806" , "rs20417" , "rs966221" )
dgnv <- enrichDGNv ( snp ) head ( dgnv )
ID Description GeneRatio BgRatio RichFactor
C0010054 C0010054 Coronary Arteriosclerosis 6/17 440/194515 0.01363636
C0151744 C0151744 Myocardial Ischemia 4/17 103/194515 0.03883495
C0031099 C0031099 Periodontitis 4/17 116/194515 0.03448276
C0007785 C0007785 Cerebral Infarction 4/17 123/194515 0.03252033
C0003850 C0003850 Arteriosclerosis 4/17 267/194515 0.01498127
C0004153 C0004153 Atherosclerosis 4/17 281/194515 0.01423488
FoldEnrichment zScore pvalue p.adjust qvalue
C0010054 156.0281 30.43647 1.568917e-12 2.761295e-10 NA
C0151744 444.3518 42.07730 1.754840e-10 1.544259e-08 NA
C0031099 394.5538 39.63952 2.839985e-10 1.583793e-08 NA
C0007785 372.0995 38.48983 3.599531e-10 1.583793e-08 NA
C0003850 171.4166 26.05143 8.145389e-09 2.867177e-07 NA
C0004153 162.8763 25.38727 9.996713e-09 2.932369e-07 NA
geneID Count
C0010054 rs5498/rs147377392/rs11053646/rs1805192/rs2230806/rs20417 6
C0151744 rs5498/rs147377392/rs11053646/rs1805192 4
C0031099 rs5498/rs909253/rs1805192/rs20417 4
C0007785 rs147377392/rs11053646/rs1805192/rs2230806 4
C0003850 rs5498/rs1805192/rs2230806/rs20417 4
C0004153 rs5498/rs1805192/rs2230806/rs20417 4
Disease gene set enrichment analysis
gseDO fuction
In the following example, in order to speedup the compilation of this document, only gene sets with size above 120 were tested and only 100 permutations were performed.
library ( DOSE ) data ( geneList ) y <- gseDO ( geneList , minGSSize = 120 ,
pvalueCutoff = 0.2 ,
pAdjustMethod = "BH" ,
verbose = FALSE )
head ( y , 3 )
ID Description setSize
DOID:612 DOID:612 primary immunodeficiency disease 194
DOID:0050117 DOID:0050117 disease by infectious agent 466
DOID:934 DOID:934 viral infectious disease 297
enrichmentScore NES pvalue p.adjust qvalue
DOID:612 0.4861389 2.195667 1.441403e-10 2.219760e-08 1.441403e-08
DOID:0050117 0.3382869 1.654190 1.060502e-07 8.165866e-06 5.302511e-06
DOID:934 0.3461519 1.635336 1.832569e-05 9.407189e-04 6.108564e-04
rank leading_edge
DOID:612 2521 tags=45%, list=20%, signal=36%
DOID:0050117 2199 tags=31%, list=18%, signal=27%
DOID:934 2197 tags=32%, list=18%, signal=27%
core_enrichment
DOID:612 55388/7153/9837/29851/6890/9636/1503/1493/7037/4173/3932/3559/6772/51311/3507/3561/917/3574/3575/919/4860/915/22806/4938/1535/3458/959/5336/11151/3702/925/4688/64135/28755/50615/974/1794/3689/5788/916/4068/3937/30009/3394/10525/100/7374/3659/939/4689/5880/7128/6891/6789/930/6573/11322/204/6850/10095/7852/8772/64170/3119/28985/1053/5971/1536/10125/8456/8625/3071/7293/4478/1380/958/5591/9437/10379/54440/3570/3978/3593/10625/29927/3558/735
DOID:0050117 4312/6279/8685/3627/4283/6362/3002/3620/6355/2921/6364/4318/3576/6890/875/1493/6352/4288/3934/59272/4599/54210/3932/80380/713/5551/133/3559/768/1230/6772/51311/6347/6402/5320/64581/4609/81611/3561/91543/6351/6590/9332/1029/1051/3574/6354/3806/7412/1535/3458/81873/959/4783/2950/3162/925/1594/50615/942/2529/51224/1991/1557/10576/9235/25939/6361/3689/1234/916/467/7096/259197/3383/6367/30009/2539/5806/6374/100/2525/1088/3600/3659/2919/6696/3549/940/58528/10541/6646/6285/6891/6396/671/7422/6059/6573/929/142/26191/4282/468/1312/7124/29949/912/1030/5329/3569/4049/7097/10096/56244/50506/2048/345/1378/5133/5743/348/4151/3119/3053/1956/2213/5971/3135/6376/9021/3596/2833/1080/356/1380/286/7133/887/958/4504/728/9402/5610/5054/4880
DOID:934 4312/6279/3627/4283/3002/3620/6355/2921/6364/3576/1493/6352/4288/3934/59272/4599/54210/3932/713/5551/3559/768/1230/6772/51311/6347/5320/4609/3561/91543/6351/6590/9332/1029/1051/3574/6354/3806/3458/959/4783/925/1594/50615/1991/9235/25939/6361/3689/1234/916/259197/3383/5806/6374/1088/3600/3659/2919/940/6285/6891/671/7422/6059/929/142/4282/468/7124/912/1030/5329/3569/7097/2048/345/5133/5743/348/4151/3119/1956/3135/6376/9021/3596/356/1380/7133/958/4504/728/9402/5610/5054
gseNCG fuction
ncg <- gseNCG ( geneList , pvalueCutoff = 0.5 ,
pAdjustMethod = "BH" ,
verbose = FALSE )
ncg <- setReadable ( ncg , 'org.Hs.eg.db' ) head ( ncg , 3 )
ID
pan-gynecological and breast pan-gynecological and breast
pan-gastric pan-gastric
breast_fibroepithelial_tumours breast_fibroepithelial_tumours
Description setSize
pan-gynecological and breast pan-gynecological and breast 43
pan-gastric pan-gastric 49
breast_fibroepithelial_tumours breast_fibroepithelial_tumours 17
enrichmentScore NES pvalue p.adjust
pan-gynecological and breast -0.5263429 -1.728298 0.003304610 0.1243685
pan-gastric -0.4993803 -1.697203 0.004015524 0.1243685
breast_fibroepithelial_tumours -0.6421576 -1.692469 0.006141654 0.1243685
qvalue rank leading_edge
pan-gynecological and breast 0.1115195 2464 tags=44%, list=20%, signal=36%
pan-gastric 0.1115195 3280 tags=49%, list=26%, signal=36%
breast_fibroepithelial_tumours 0.1115195 2700 tags=59%, list=22%, signal=46%
core_enrichment
pan-gynecological and breast ATM/ZC3H13/NIPBL/SPOP/ARID1A/RASA1/RB1/RNF43/MAP2K4/NF1/CTNNB1/TP53/PIK3R1/CDKN1B/CCND1/ARID5B/MAP3K1/TBX3/GATA3
pan-gastric BCOR/SOX9/TCF7L2/ATM/CALD1/SEMG2/HTR7/ARID1A/RASA1/RB1/TTBK2/RNF43/CTNNB1/TP53/BCL9/SMAD3/APC/ZFP36L2/TGFBR2/MUC6/MAP3K1/CACNA1C/ATP8B1/CYP4B1
breast_fibroepithelial_tumours BCOR/SETD2/RB1/PCNX4/NF1/TP53/RARA/SYNE1/MAP3K1/ERBB4
gseDGN fuction
dgn <- gseDGN ( geneList , pvalueCutoff = 0.2 ,
pAdjustMethod = "BH" ,
verbose = FALSE )
dgn <- setReadable ( dgn , 'org.Hs.eg.db' ) head ( dgn , 3 )
ID Description setSize enrichmentScore
C0024266 C0024266 Lymphocytic Choriomeningitis 120 0.5712593
C4721414 C4721414 Mantle cell lymphoma 368 0.4107437
C0205682 C0205682 Waist-Hip Ratio 401 -0.4425633
NES pvalue p.adjust qvalue rank
C0024266 2.405091 1e-10 2.05275e-07 1.754737e-07 2579
C4721414 1.980385 1e-10 2.05275e-07 1.754737e-07 1745
C0205682 -1.953671 1e-10 2.05275e-07 1.754737e-07 2011
leading_edge
C0024266 tags=48%, list=21%, signal=38%
C4721414 tags=26%, list=14%, signal=23%
C0205682 tags=28%, list=16%, signal=24%
core_enrichment
C0024266 S100A9/CXCL10/CXCL9/EZH2/GZMB/ICOS/USP18/CXCL8/CTLA4/TREM1/PRF1/ADM/CA9/STAT1/CCL2/SELL/CDKN2A/IL7/IL7R/IFNG/CCR5/IL27RA/SH2D1A/FCER1G/CDK2AP2/CPVL/CD27/PSMB10/PTPN22/SLAMF1/KDM1A/TNF/IL6/FGL2/TLR2/RPAIN/NELFCD/PDCD1/WAS/HIF1A/ATP5F1B/FCGR2B/EGR2/STX11/CXCR3/TYROBP/YME1L1/SOSTDC1/PTPN2/TRAF1/HNF1A/IRF9/PML/NR0B2/IL2/TOX/AGFG1
C4721414 CDC20/MELK/E2F8/APOBEC3B/PBK/TPX2/RAD51AP1/DUSP2/CDT1/EZH2/AURKB/CHEK1/AURKA/CCNB1/PSAT1/SOX11/PRAME/CDC6/PLK1/MMP9/EIF4EBP1/SPIB/RAD51/CD38/MMP7/MCM6/CTSC/LCK/MNX1/SKP2/STAT1/PRDM1/MS4A4A/IGK/MYC/PCNA/IFI27/PSMG1/CCR7/GMNN/E2F1/CDKN2A/PSMB9/NME1/LTB/IGHD/CD40LG/LAIR1/IGF2BP3/LBR/COL11A2/MSH2/CD79B/APRT/NSD2/CDK4/PTPRC/PLSCR1/CCR5/G6PD/CHEK2/HILPDA/DCK/PIM2/WNT3/CD6/CD28/MTAP/PRDX1/MRC1/TUBB3/VEGFA/CD19/HACD1/SOX4/PMCH/ST14/PARP1/TCL1A/DNMT1/IGLL5/SYK/TNF/MYCN/CD1D/NXT1/CDKN2B/RANGAP1/IL6/LTA/PSMD2/CXCR4/BCR/FCER2/FADD/PTGS2
C0205682 RETREG3/JMJD1C/SH2B1/BDNF/ARHGEF26/PDE5A/BPTF/SMAD3/TTC39A/ATP2B1/ARID4A/HOXC4/NID1/LAMA4/LRRC36/NUDT18/ANKRD28/HECTD4/COL11A1/MEIS1/INSR/CUL9/NRIP3/BCL2/CD34/EZH1/DYM/NDST1/COL15A1/VGLL3/CCND1/ZCCHC10/HOXC6/RAB26/QTRT1/MEIS2/ARID5B/AHNAK/FGF1/CAPRIN2/LAMB1/CPEB3/ELOVL4/CDADC1/PDE8B/ZNF268/NRP1/SYTL2/NR5A2/DGLUCY/SEMA3B/NID2/SIK3/PRR5L/FGF2/COL8A1/RAPGEF3/RBM6/CDH13/JCAD/NAV3/TRIM8/PPIEL/PTPRG/NBL1/CALCRL/PPL/LPL/BCKDHB/MAPKBP1/CNTLN/BBS4/P4HTM/FTO/PDZRN4/PDGFC/SGCD/NRXN3/AFF3/IGF1R/ABCC8/MPPED2/COL5A1/COL6A2/LOXL1/CYP21A2/LTBP2/TTC28/PATJ/PCSK5/WNT4/TTC12/NISCH/ASTN2/TCEA2/MN1/SETBP1/TAOK1/MAST4/ITGA7/ITGBL1/COL14A1/C1QTNF3/ZNF423/IQCH/MYH11/ADH1B/ABLIM3/MAPT/STC2/TFAP2B/CYBRD1/SCUBE2
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