eQTLMAPT: Fast and Accurate eQTL Mediation Analysis With Efficient Permutation Testing Approaches
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Xiaoli Liu | Yadong Wang | Yongzhuang Liu | Jiajie Peng | Qidi Peng | Bo Liu | Tao Wang | Jiajie Peng | Yadong Wang | Bo Liu | Yongzhuang Liu | Xiaoli Liu | Tao Wang | Qidi Peng
[1] Xiaoyu Wang,et al. Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data , 2018, BMC Bioinformatics.
[2] Jiajie Peng,et al. InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk , 2018, BMC Genomics.
[3] Andrew E. Jaffe,et al. Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .
[4] P. Sham,et al. Model-Free Analysis and Permutation Tests for Allelic Associations , 1999, Human Heredity.
[5] D. Reich,et al. Population Structure and Eigenanalysis , 2006, PLoS genetics.
[6] Liang Cheng,et al. Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study , 2018, Front. Genet..
[7] Marcel J. T. Reinders,et al. Fewer permutations, more accurate P-values , 2009, Bioinform..
[8] Jie Sun,et al. DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function , 2018, Bioinform..
[9] Carson C Chow,et al. Second-generation PLINK: rising to the challenge of larger and richer datasets , 2014, GigaScience.
[10] Daniel Marbach,et al. Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases , 2016, Nature Methods.
[11] Liang Cheng,et al. gutMDisorder: a comprehensive database for dysbiosis of the gut microbiota in disorders and interventions , 2019, Nucleic acids research.
[12] Andrey A. Shabalin,et al. Matrix eQTL: ultra fast eQTL analysis via large matrix operations , 2011, Bioinform..
[13] Erdogan Taskesen,et al. Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.
[14] H. Abdi,et al. Principal component analysis , 2010 .
[15] Vartan Choulakian,et al. Goodness-of-Fit Tests for the Generalized Pareto Distribution , 2001, Technometrics.
[16] P. Visscher,et al. 10 Years of GWAS Discovery: Biology, Function, and Translation. , 2017, American journal of human genetics.
[17] Robert Bjornson,et al. Large-Scale trans-eQTLs Affect Hundreds of Transcripts and Mediate Patterns of Transcriptional Co-regulation. , 2017, American journal of human genetics.
[18] Christopher D. Brown,et al. Identification, Replication, and Functional Fine-Mapping of Expression Quantitative Trait Loci in Primary Human Liver Tissue , 2011, PLoS genetics.
[19] J. Schneider,et al. Overview and findings from the religious orders study. , 2012, Current Alzheimer research.
[20] Hans-Ulrich Klein,et al. Descriptor : A multi-omic atlas of the human frontal cortex for aging and Alzheimer ’ s disease research , 2018 .
[21] Qinghua Guo,et al. LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse , 2018, Nucleic Acids Res..
[22] A. Chen-Plotkin,et al. The Post-GWAS Era: From Association to Function. , 2018, American journal of human genetics.
[23] Jiajie Peng,et al. Identifying emerging phenomenon in long temporal phenotyping experiments , 2019, Bioinform..
[24] Stephen B. Montgomery,et al. Cis and Trans Effects of Human Genomic Variants on Gene Expression , 2014, PLoS genetics.
[25] J. Schneider,et al. Overview and findings from the rush Memory and Aging Project. , 2012, Current Alzheimer research.
[26] AbdiHervé,et al. Principal Component Analysis , 2010, Essentials of Pattern Recognition.
[27] John D. Storey,et al. Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[28] Meng Zhou,et al. MetSigDis: a manually curated resource for the metabolic signatures of diseases , 2019, Briefings Bioinform..
[29] M. Peters,et al. Systematic identification of trans eQTLs as putative drivers of known disease associations , 2013, Nature Genetics.
[30] Charles C. White,et al. A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease , 2018, Nature Neuroscience.
[31] R. Durbin,et al. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses , 2012, Nature Protocols.
[32] Yadong Wang,et al. FSM: Fast and Scalable Network Motif Discovery for Exploring Higher-order Network Organizations. , 2020, Methods.
[33] Liang Cheng,et al. Human Disease System Biology. , 2018, Current gene therapy.
[34] E. Dermitzakis,et al. Expression quantitative trait loci: present and future , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.
[35] Jianye Hao,et al. A learning-based framework for miRNA-disease association identification using neural networks , 2018, bioRxiv.
[36] Nicola J. Rinaldi,et al. Genetic effects on gene expression across human tissues , 2017, Nature.
[37] Jeroen F. J. Laros,et al. Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories , 2013, Nature Biotechnology.
[38] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[39] Xiaoyu Wang,et al. Combining Gene Ontology with Deep Neural Networks to Enhance the Clustering of Single Cell RNA-Seq Data , 2018 .
[40] Fan Yang,et al. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis , 2016, bioRxiv.
[41] Lude Franke,et al. Mediation Analysis Demonstrates That Trans-eQTLs Are Often Explained by Cis-Mediation: A Genome-Wide Analysis among 1,800 South Asians , 2014, PLoS genetics.
[42] David E Hill,et al. Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits. , 2017, American journal of human genetics.
[43] Jingyuan Fu,et al. Trans-eQTLs Reveal That Independent Genetic Variants Associated with a Complex Phenotype Converge on Intermediate Genes, with a Major Role for the HLA , 2011, PLoS genetics.
[44] Emmanouil T. Dermitzakis,et al. Fast and efficient QTL mapper for thousands of molecular phenotypes , 2015, bioRxiv.
[45] Wanying Xu,et al. OAHG: an integrated resource for annotating human genes with multi-level ontologies , 2016, Scientific Reports.
[46] Peggy Hall,et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations , 2013, Nucleic Acids Res..
[47] Hui Hu,et al. AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors , 2018, Nucleic Acids Res..
[48] Jiajie Peng,et al. Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder , 2019, Front. Genet..