Interactive Exploration, Analysis, and Visualization of Complex Phenome–Genome Datasets with ASPIREdb

Human Mutation

Volumn 37, Issue 8, 2016, Pages 719-726

  Tan, Powell Patrick Cheng ^a   Rogic, Sanja ^a   Zoubarev, Anton ^a   McDonald, Cameron ^a   Lui, Frances ^a   Charathsandran, Gayathiri ^a   Jacobson, Matthew ^a   Belmadani, Manuel ^a   Leong, Justin ^a   Van Rossum, Thea ^a   Portales Casamar, Elodie ^a   Qiao, Ying ^b   Calli, Kristina ^b   Liu, Xudong ^c,d   Hudson, Melissa ^c   Rajcan Separovic, Evica ^b   Lewis, M E Suzanne ^b   Pavlidis, Paul ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c QUEEN S UNIVERSITY   (Canada)

^d Ongwanada Resource Centre   (Canada)

Author keywords

computational biology; genotype phenotype; visualization; WES; WGS; whole exome sequencing; whole genome sequencing

Indexed keywords

ARTICLE; EXOME; GENE INTERACTION; GENE SEQUENCE; GENETIC VARIATION; GENOMICS; GENOTYPE PHENOTYPE CORRELATION; PHENOME; PRIORITY JOURNAL; REFERENCE DATABASE; SEQUENCE ANALYSIS;

EID: 84978032269     PISSN: 10597794     EISSN: 10981004     Source Type: Journal    
DOI: 10.1002/humu.23011     Document Type: Article

References (33)

1. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. 2010. A method and server for predicting damaging missense mutations. Nat Methods 7:248–249.
2. Andrews T, Meader S, Vulto-van Silfhout A, Taylor A, Steinberg J, Hehir-Kwa J, Pfundt R, de Leeuw N, de Vries BBA, Webber C. 2015. Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders. PLoS Genet 11:e1005012.
3. Banerjee-Basu S, Packer A. 2010. SFARI gene: an evolving database for the autism research community. Dis Model Mech 3:133–135.
4. Bernier R, Golzio C, Xiong B, Stessman HA, Coe BP, Penn O, Witherspoon K, Gerdts J, Baker C, Vulto-van Silfhout AT, Schuurs-Hoeijmakers JH, Fichera M, et al. 2014. Disruptive CHD8 mutations define a subtype of autism early in development. Cell 158:263–276.
5. Bernier R, Steinman KJ, Reilly B, Wallace AS, Sherr EH, Pojman N, Mefford HC, Gerdts J, Earl R, Hanson E, Goin-Kochel RP, Berry L, et al. 2016. Clinical phenotype of the recurrent 1q21.1 copy-number variant. Genet Med 18:341–349.
6. Bragin E, Chatzimichali EA, Wright CF, Hurles ME, Firth HV, Bevan AP, Swaminathan GJ. 2013. DECIPHER: database for the interpretation of phenotype-linked plausibly pathogenic sequence and copy-number variation. Nucleic Acids Res 42:D993–D1000.
7. Coe BP, Witherspoon K, Rosenfeld JA, Van Bon BWM, Vulto-van Silfhout AT, Bosco P, Friend KL, Baker C, Buono S, Vissers LELM, Schuurs-Hoeijmakers JH, Hoischen A, et al. 2014. Refining analyses of copy number variation identifies specific genes associated with developmental delay. Nat Genet 46:1063–1071.
8. Gillis J, Mistry M, Pavlidis P. 2010. Gene function analysis in complex data sets using ErmineJ. Nat Protoc 5:1148–1159.
9. Groza T, Köhler S, Moldenhauer D, Vasilevsky N, Baynam G, Zemojtel T, Schriml LM, Kibbe WA, Schofield PN, Beck T, Vasant D, Brookes AJ, et al. 2015. The Human Phenotype Ontology: semantic unification of common and rare disease. Am J Hum Genet 97:111–124.
10. Hammond P, Forster-Gibson C, Chudley AE, Allanson JE, Hutton TJ, Farrell SA, McKenzie J, Holden JJA, Lewis MES. 2008. Face–brain asymmetry in autism spectrum disorders. Mol. Psychiatry 13:614–623.
11. Helsmoortel C, Vulto-van Silfhout AT, Coe BP, Vandeweyer G, Rooms L, Ende J van den, Schuurs-Hoeijmakers JHM, Marcelis CL, Willemsen MH, Vissers LELM, Yntema HG, Bakshi M, et al. 2014. A SWI/SNF-related autism syndrome caused by de novo mutations in ADNP. Nat Genet 46:380–384.
12. Iossifov I, Ronemus M, Levy D, Wang Z, Hakker I, Rosenbaum J, Yamrom B, Lee Y, Narzisi G, Leotta A, Kendall J, Grabowska E, et al. 2012. De novo gene disruptions in children on the autistic spectrum. Neuron 74:285–299.
13. Juan L, Liu Y, Wang Y, Teng M, Zang T, Wang Y. 2015. Family genome browser: visualizing genomes with pedigree information. Bioinformatics 31:2262–2268.
14. Kaufman L, Rousseeuw PJ. 2009. Finding groups in data: an introduction to cluster analysis. John Wiley & Sons.
15. Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J. 2014. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet 46:310–315.
16. Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, Maglott DR. 2014. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 42:D980–D985.
17. MacDonald JR, Ziman R, Yuen RKC, Feuk L, Scherer SW. 2014. The Database of Genomic Variants: a curated collection of structural variation in the human genome. Nucleic Acids Res 42:D986–D992.
18. Mann HB, Whitney DR. 1947. On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50–60.
19. Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE, Sabo A, Lin C-F, Stevens C, Wang L-S, Makarov V, Polak P, Yoon S, et al. 2012. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485:242–245.
20. Ng PC, Henikoff S. 2003. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res 31:3812–3814.
21. Paila U, Chapman BA, Kirchner R, Quinlan AR. 2013. GEMINI: integrative exploration of genetic variation and genome annotations. PLoS Comput Biol 9:e1003153.
22. Portales-Casamar E, Ch'ng C, Lui F, St-Georges N, Zoubarev A, Lai AY, Lee M, Kwok C, Kwok W, Tseng L, Pavlidis P. 2013. Neurocarta: aggregating and sharing disease-gene relations for the neurosciences. BMC Genomics 14:129.
23. Qiao Y, Mercier E, Dastan J, Hurlburt J, McGillivray B, Chudley AE, Farrell S, Bernier FP, Lewis MS, Pavlidis P, Rajcan-Separovic E. 2014. Copy number variants (CNVs) analysis in a deeply phenotyped cohort of individuals with intellectual disability (ID). BMC Med Genet 15:82.
24. Rosenbloom KR, Armstrong J, Barber GP, Casper J, Clawson H, Diekhans M, Dreszer TR, Fujita PA, Guruvadoo L, Haeussler M, Harte RA, Heitner S, et al. 2015. The UCSC Genome Browser database: 2015 update. Nucleic Acids Res 43:D670–D681.
25. Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, Ercan-Sencicek AG, DiLullo NM, Parikshak NN, Stein JL, Walker MF, Ober GT, et al. 2012. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485:237–241.
26. Sherry ST, Ward M-H, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K. 2001. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 29:308–311.
27. Smedley D, Haider S, Ballester B, Holland R, London D, Thorisson G, Kasprzyk A. 2009. BioMart—biological queries made easy. BMC Genomics 10:22.
28. Vandeweyer G, Van Laer L, Loeys B, Van den Bulcke T, Kooy RF. 2014. VariantDB: a flexible annotation and filtering portal for next generation sequencing data. Genome Med 6:74.
29. Vulto-van Silfhout AT, Hehir-Kwa JY, Van Bon BWM, Schuurs-Hoeijmakers JHM, Meader S, Hellebrekers CJM, Thoonen IJM, Brouwer APM de, Brunner HG, Webber C, Pfundt R, de Leeuw N, et al. 2013. Clinical significance of de novo and inherited copy-number variation. Hum Mutat 34:1679–1687.
30. Wang J, Liao J, Zhang J, Cheng W-Y, Hakenberg J, Ma M, Webb BD, Ramasamudram-chakravarthi R, Karger L, Mehta L, Kornreich R, Diaz GA, et al. 2015. ClinLabGeneticist: a tool for clinical management of genetic variants from whole exome sequencing in clinical genetic laboratories. Genome Med 7:77.
31. Webber C. 2011. Functional enrichment analysis with structural variants: pitfalls and strategies. Cytogenet Genome Res 135:277–285.
32. Yates F. 1934. Contingency tables involving small numbers and the χ2 test. Suppl J R Stat Soc 1:217–235.
33. Zoubarev A, Hamer KM, Keshav KD, McCarthy EL, Santos JRC, Van Rossum T, McDonald C, Hall A, Wan X, Lim R, Gillis J, Pavlidis P. 2012. Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data. Bioinformatics 28:2272–2273.