Systematic permutation testing in GWAS pathway analyses: identification of genetic networks in dilated cardiomyopathy and ulcerative colitis
Open accessAbstract
BACKGROUND: Genome wide association studies (GWAS) are applied to identify genetic loci, which are associated with complex traits and human diseases. Analogous to the evolution of gene expression analyses, pathway analyses have emerged as important tools to uncover functional networks of genome-wide association data. Usually, pathway analyses combine statistical methods with a priori available biological knowledge. To determine significance thresholds for associated pathways, correction for multiple testing and over-representation permutation testing is applied. RESULTS: We systematically investigated the impact of three different permutation test approaches for over-representation analysis to detect false positive pathway candidates and evaluate them on genome-wide association data of Dilated Cardiomyopathy (DCM) and Ulcerative Colitis (UC). Our results provide evidence that the gold standard - permuting the case-control status - effectively improves specificity of GWAS pathway analysis. Although permutation of SNPs does not maintain linkage disequilibrium (LD), these permutations represent an alternative for GWAS data when case-control permutations are not possible. Gene permutations, however, did not add significantly to the specificity. Finally, we provide estimates on the required number of permutations for the investigated approaches. CONCLUSIONS: To discover potential false positive functional pathway candidates and to support the results from standard statistical tests such as the Hypergeometric test, permutation tests of case control data should be carried out. The most reasonable alternative was case-control permutation, if this is not possible, SNP permutations may be carried out. Our study also demonstrates that significance values converge rapidly with an increasing number of permutations. By applying the described statistical framework we were able to discover axon guidance, focal adhesion and calcium signaling as important DCM-related pathways and Intestinal immune network for IgA production as most significant UC pathway.
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The permutation test provides control over family-wise error rate, is nonparametric, automatically adjusts to the degree of correlation between tests, and does not make specific assumptions about the shape of the population distribution.
“The permutation test provides control over family-wise error rate, is nonparametric, automatically adjusts to the degree of correlation between tests, and does not make specific assumptions about the shape of the population distribution from which the observations have been derived (Backes et al. 2014).”
From Joint attention and brain functional connectivity in infants and toddlers (2017) · cites this paper as Backes et al. 2014
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232 · see citing works
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108 · see citing works
Complement factor H polymorphism in age-related macular degeneration
Klein, R. J., Zeiss, C., Chew, E. Y., Tsai, J.-Y., Sackler, R. S., Haynes, C., Henning, A. K., SanGiovanni, J. P., Mane, S. M., Mayne, S. T., et al. (2005) · Science · doi:10.1126/science.1109557 · Cited by 4,492 · see citing works
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationGenomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162 · see citing works
Complement factor H variant increases the risk of age-related macular degeneration
Haines, J. L., Hauser, M. A., Schmidt, S., Scott, W. K., Olson, L. M., Gallins, P., Spencer, K. L., Kwan, S. Y., Noureddine, M., Gilbert, J. R., et al. (2005) · Science · doi:10.1126/science.1110359 · Cited by 2,424 · see citing works
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges
Khatri, P., Sirota, M., & Butte, A. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002375 · Cited by 1,569 · see citing works
A systems biology approach for pathway level analysisPreprint
Drăghici, S., Khatri, P., Tarca, A. L., Amin, K., Done, A., Voichiţa, C., Georgescu, C., & Romero, R. J. (2007) · Genome Research · doi:10.1101/gr.6202607 · Cited by 1,250 · see citing works
TRANSFAC: an integrated system for gene expression regulation
Wingender, E. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.316 · Cited by 1,249 · see citing works
Pathway-Based Approaches for Analysis of Genomewide Association Studies
Wang, K., Li, M., & Bućan, M. (2007) · The American Journal of Human Genetics · doi:10.1086/522374 · Cited by 858 · see citing works
On testing the significance of sets of genes
Efron, B., & Tibshirani, R. J. (2007) · The Annals of Applied Statistics · doi:10.1214/07-aoas101 · Cited by 785 · see citing works
Analysing biological pathways in genome-wide association studies
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2884 · Cited by 757 · see citing works
Bock-Marquette, I., Saxena, A., White, M. D., Michael DiMaio, J., & Srivastava, D. (2004) · Nature · doi:10.1038/nature03000 · Cited by 657 · see citing works
Sympathetic Nervous System Activation in Human Heart Failure
Floras, J. S. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2009.03.061 · Cited by 552 · see citing works
Intestinal IgA synthesis: regulation of front-line body defences
Fagarasan, S., & Honjo, T. (2003) · Nature reviews. Immunology · doi:10.1038/nri982 · Cited by 505 · see citing works
Karp, P. D. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.59 · Cited by 414 · see citing works
Secretory IgA: Designed for Anti-Microbial Defense
Brandtzæg, P. (2013) · Frontiers in Immunology · doi:10.3389/fimmu.2013.00222 · Cited by 382 · see citing works
Gene Ontology Analysis of GWA Study Data Sets Provides Insights into the Biology of Bipolar Disorder
Holmans, P., Green, E. K., Pahwa, J. S., Ferreira, M. A. R., Purcell, S. M., Sklar, P., Owen, M. J., O'Donovan, M. C., & Craddock, N. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.05.011 · Cited by 378 · see citing works
GeneTrail--advanced gene set enrichment analysis
Backes, C., Keller, A., Küntzer, J., Kneissl, B., Comtesse, N., Elnakady, Y. A., Müller, R., Meese, E. U., & Lenhof, H. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm323 · Cited by 341 · see citing works
Self-citationFerguson, D. W., Berg, W. J., Sanders, J. S., & Kempf, J. S. (1990) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(90)90544-y · Cited by 269 · see citing works
An integer linear programming approach for finding deregulated subgraphs in regulatory networks
Backes, C., Rurainski, A., Klau, G. W., Müller, O. J., Stöckel, D., Gerasch, A., Küntzer, J., Maisel, D., Ludwig, N., Hein, M., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1227 · Cited by 259 · see citing works
Self-citationFewer permutations, more accurate P -values
Knijnenburg, T., Wessels, L. F. A., Reinders, M. J. T., & Ilya Shmulevich, C. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp211 · Cited by 221 · see citing works
Bendig, G., Grimmler, M., Huttner, I. G., Wessels, G., Dahme, T., Just, S., Trano, N., Katus, H. A., Fishman, M. C., & Rottbauer, W. (2006) · Genes & Development · doi:10.1101/gad.1448306 · Cited by 207 · see citing works
Self-citationEllinghaus, D., Folseraas, T., Holm, K., Ellinghaus, E., Melum, E., Balschun, T. C., Laerdahl, J. K., Shiryaev, A., Gotthardt, D. N., Weismüller, T. J., et al. (2012) · Hepatology · doi:10.1002/hep.25977 · Cited by 195 · see citing works
Self-citationA genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy
Meder, B., Rühle, F., Weis, T., Homuth, G., Keller, A., Franke, J., Peil, B., Bermejo, J. L., Frese, K., Huge, A., et al. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht251 · Cited by 172 · see citing works
Self-citationA Slit/miR-218/Robo regulatory loop is required during heart tube formation in zebrafish
Fish, J. E., Wythe, J. D., Xiao, T., Bruneau, B. G., Stainier, D. Y. R., Srivastava, D., & Woo, S. (2011) · Development · doi:10.1242/dev.060046 · Cited by 150 · see citing works
Microbiome and immunological interactions
Kelly, D., & Mulder, I. E. (2012) · Nutrition Reviews · doi:10.1111/j.1753-4887.2012.00498.x · Cited by 127 · see citing works
Calculating the Statistical Significance of Changes in Pathway Activity From Gene Expression Data
Rahnenführer, J., Domingues, F. S., Maydt, J., & Lengauer, T. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1055 · Cited by 125 · see citing works
Analysis of Gene Sets Based on the Underlying Regulatory Network
Shojaie, A., & Michailidis, G. C. (2009) · Journal of Computational Biology · doi:10.1089/cmb.2008.0081 · Cited by 123 · see citing works
Liu, G., Jiang, Y., Wang, P., Feng, R., Jiang, N., Chen, X., Song, H., & Chen, Z. (2011) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2011.07547.x · Cited by 83 · see citing works
Insights into Pancreatic Cancer Etiology from Pathway Analysis of Genome-Wide Association Study Data
Wei, P., Tang, H., & Li, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046887 · Cited by 82 · see citing works
GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments
Keller, A., Backes, C., Al-Awadhi, M., Gerasch, A., Küntzer, J., Kohlbacher, O., Kaufmann, M., & Lenhof, H. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-552 · Cited by 81 · see citing works
Self-citationIntercellular and extracellular mechanotransduction in cardiac myocytes
Kresh, J. Y., & Chopra, A. (2011) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-011-0954-1 · Cited by 71 · see citing works
Saccone, S. F., Bolze, R., Thomas, P. D., Quan, J., Mehta, G., Deelman, E., Tischfield, J. A., & Rice, J. P. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq513 · Cited by 67 · see citing works
Pathways of Distinction Analysis: A New Technique for Multi–SNP Analysis of GWAS Data
Braun, R., & Buetow, K. H. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002101 · Cited by 63 · see citing works
The Genome Knowledgebase: A Resource for Biologists and BioinformaticistsPreprint
JOSHI-TOPE, G., Västrik, I., Gopinath, G., Matthews, L. R., Schmidt, E., Gillespie, M. E., D’Eustachio, P., Jassal, B., Lewis, S., Wu, G., et al. (2003) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2003.68.237 · Cited by 60 · see citing works
Mommersteeg, M. T. M., Andrews, W. D., Ypsilanti, A. R., Zelina, P., Yeh, M. L., Norden, J., Kispert, A., Chédotal, A., Christoffels, V. M., & Parnavelas, J. G. (2012) · Circulation Research · doi:10.1161/circresaha.112.277426 · Cited by 60 · see citing works
Integrins, Focal Adhesions, and Cardiac Fibroblasts
Manso, A. M., Kang, S., & Ross, R. S. (2009) · Journal of Investigative Medicine · doi:10.2310/jim.0b013e3181c5e61f · Cited by 59 · see citing works
Comparisons of seven algorithms for pathway analysis using the WTCCC Crohn's Disease dataset
Gui, H., Li, M., Sham, P. C., & Cherny, S. S. (2011) · BMC Research Notes · doi:10.1186/1756-0500-4-386 · Cited by 57 · see citing works
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Keller, A., Backes, C., & Lenhof, H. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-290 · Cited by 54 · see citing works
Self-citationA novel algorithm for detecting differentially regulated paths based on gene set enrichment analysis
Keller, A., Backes, C., Gerasch, A., Kaufmann, M., Kohlbacher, O., Meese, E. U., & Lenhof, H. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp510 · Cited by 50 · see citing works
Self-citationLiu, Y., Maxwell, S., Feng, T., Zhu, X., Elston, R. C., Koyutürk, M., & Chance, M. R. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-s3-s15 · Cited by 48 · see citing works
Meder, B., Huttner, I. G., Sedaghat‐Hamedani, F., Just, S., Dahme, T., Frese, K., Vogel, B., Köhler, D., Kloos, W., Rudloff, J., et al. (2011) · Molecular and Cellular Biology · doi:10.1128/mcb.05269-11 · Cited by 45 · see citing works
Self-citationMiwa, K., Lee, J., Takagishi, Y., Tobias Opthof, A., Fu, X., Hirabayashi, M., Watabe, K., Jimbo, Y., Kodama, I., & Komuro, I. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065202 · Cited by 45 · see citing works
Expression of Slit and Robo genes in the developing mouse heart
Médioni, C., Bertrand, N., Mesbah, K., Hudry, B., Dupays, L., Wolstein, O., Washkowitz, A. J., Papaioannou, V. E., Mohun, T. J., Harvey, R. P., et al. (2010) · Developmental Dynamics · doi:10.1002/dvdy.22449 · Cited by 42 · see citing works
Vascular endothelial-derived semaphorin 3 inhibits sympathetic axon growth
Damon, D. H. (2005) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.01232.2004 · Cited by 26 · see citing works
Blood gene expression signatures associate with heart failure outcomes
VanBuren, P., Ma, J., Chao, S., Mueller, E., Schneider, D. J., & Liew, C. (2011) · Physiological Genomics · doi:10.1152/physiolgenomics.00175.2010 · Cited by 22 · see citing works
Ferguson, J. P., Cho, J. H., & Zhao, H. (2012) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/1544-6115.1660 · Cited by 20 · see citing works
NetworkTrail—a web service for identifying and visualizing deregulated subnetworks
Stöckel, D., Müller, O. J., Kehl, T., Gerasch, A., Backes, C., Rurainski, A., Keller, A., Kaufmann, M., & Lenhof, H. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt204 · Cited by 13 · see citing works
Self-citationCandidate Pathway Based Analysis for Cleft Lip with or without Cleft Palate
Zhang, T.-X., Beaty, T. H., & Ruczinski, I. (2012) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1717 · Cited by 10 · see citing works
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Eggebrecht, A. T., Elison, J. T., Feczko, E., Todorov, A., Wolff, J. J., Kandala, S., Adams, C. M., Snyder, A. Z., Lewis, J. D., Estes, A. M., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhw403 · Cited by 156 · see citing works
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Wheelock, M. D., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., Eggebrecht, A. T., & Thomason, M. E. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100632 · Cited by 126 · see citing works
Marek, S. A., Tervo‐Clemmens, B., Nielsen, A. N., Wheelock, M. D., Miller, R. L., Laumann, T. O., Earl, E., Foran, W., Cordova, M., Doyle, O. J., et al. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100706 · Cited by 122 · see citing works
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Thomason, M. E., Hect, J. L., Rauh, V. A., Trentacosta, C., Wheelock, M. D., Eggebrecht, A. T., Espinoza-Heredia, C., & Burt, S. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.017 · Cited by 94 · see citing works
McKinnon, C., Eggebrecht, A. T., Todorov, A. A., Wolff, J. J., Elison, J. T., Adams, C. M., Snyder, A. Z., Estes, A. M., Zwaigenbaum, L., Botteron, K. N., et al. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.09.008 · Cited by 95 · see citing works
Thomason, M. E., Hect, J. L., Waller, R. E., & Curtin, P. C. P. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01066-7 · Cited by 78 · see citing works
Altered functional network connectivity relates to motor development in children born very preterm
Wheelock, M. D., Austin, N. C., Bora, S., Eggebrecht, A. T., Melzer, T. R., Woodward, L. J., & Smyser, C. D. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.051 · Cited by 64 · see citing works
Mills, B. D., Grayson, D. S., Shunmugavel, A., Miranda-Domínguez, Ó., Feczko, E., Earl, E., Neve, K. A., & Fair, D. A. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.2910-17.2018 · Cited by 36 · see citing works
Zhang, L., Zhang, G., Lu, Y., Gao, J., Qin, Z., Xu, S., Wang, Z., Xu, Y., Yang, Y. L., Zhang, J., et al. (2023) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.17789 · Cited by 30 · see citing works
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Perino, M. T., Myers, M. J., Wheelock, M. D., Yu, Q., Harper, J., Manhart, M., Gordon, E. M., Eggebrecht, A. T., Pine, D. S., Barch, D. M., et al. (2021) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2021.05.007 · Cited by 18 · see citing works
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Zhong, X., Hua, L., Yang, Y., Shi, T., Liu, W., Tuo, X., Yu, L., Cao, X., & Yang, F. (2019) · BioMed Research International · doi:10.1155/2019/9565794 · Cited by 14 · see citing works
Zhao, H., Nyholt, D. R., Yang, Y., Yang, Y., & Yang, Y. (2017) · Scientific Reports · doi:10.1038/s41598-017-03826-2 · Cited by 11 · see citing works
Qian, D. C., Molfese, D. L., Jin, J. L., Titus, A., He, Y., Li, Y., Vaissié, M., Viswanath, H., Baldwin, P. R., Krahe, R., et al. (2017) · BMC Genomics · doi:10.1186/s12864-017-4124-5 · Cited by 9 · see citing works
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Self-citationWan, L., Zhang, Y., He, Y., Wang, Y., Guo, S., Zhao, X., Feng, Y., Song, Z., Zou, Y., He, W., et al. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103155 · Cited by 5 · see citing works
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Gilbert, K., Wheelock, M. D., Kandala, S., Eggebrecht, A. T., Luby, J. L., & Barch, D. M. (2021) · Cortex · doi:10.1016/j.cortex.2021.05.015 · Cited by 4 · see citing works
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- Authors
- Backes, C., Rühle, F., Stoll, M., Haas, J., Frese, K., Franke, A., Lieb, W., Wichmann, H.-E., Weis, T., Kloos, W., Lenhof, H.-P., Meese, E., Katus, H., Meder, B., & Keller, A.
- Affiliations
- Saarland University (DE)
- University of Münster (DE)
- University Hospital Heidelberg (DE)
- Christian-Albrechts-Universität zu Kiel (DE)
- Helmholtz Munich (DE)
- Corresponding author
- Keller, Andreas
- ORCID
- Venue
- BMC Genomics
- Published
- 2014-07-22
- Volume
- 15
- Issue
- 1
- Pages
- 622-622
- ISSN
- 1471-2164 (ISSN-L)
- PMC
- PMC4223581
- OpenAlex
- W2150472995
- Cited by
- 26
- References
- 55
- Citations by year
- 2026: 1 · 2025: 2 · 2023: 2 · 2021: 4 · 2019: 7 · 2018: 4 · 2017: 3 · 2016: 1 · 2015: 2
- FWCI
- 0.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Genomics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- heiDOK (Heidelberg University) (acceptedVersion, other-oa)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
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- Funders
- Deutsches Zentrum für Herz-Kreislaufforschung
- European Commission
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- permutation tests, pathway analysis, over-representation analysis, dilated cardiomyopathy, ulcerative colitis, multiple testing correction, hypergeometric test, gene networks, axon guidance, focal adhesions, calcium signaling
- MeSH terms
- Cardiomyopathy, Dilated, Colitis, Ulcerative, Humans, Signal Transduction, Polymorphism, Single Nucleotide, Genomics, Gene Regulatory Networks, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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