ArticleBioinformatics (Oxford, England)2012
GenomeRunner: automating genome exploration.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
22 citing papers in PubMed.
- Oklahoma Nathan Shock Aging Center - assessing the basic biology of aging from genetics to protein and function.GeroScience · 2021Article
- DNA Methylation in Babies Born to Nonsmoking Mothers Exposed to Secondhand Smoke during Pregnancy: An Epigenome-Wide Association Study.Environmental health perspectives · 2021Article
- Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines.GigaScience · 2021Article
- Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer.Scientific reports · 2020Article
- TADCompare: An R Package for Differential and Temporal Analysis of Topologically Associated Domains.Frontiers in genetics · 2020Article
- Trans-Ethnic Mapping ofInternational journal of molecular sciences · 2018Article
- LOLAweb: a containerized web server for interactive genomic locus overlap enrichment analysis.Nucleic acids research · 2018Article
- Sexually divergent DNA methylation patterns with hippocampal aging.Aging cell · 2017Article
- Effects of DNA Methylation on Progression to Interstitial Fibrosis and Tubular Atrophy in Renal Allograft Biopsies: A Multi-Omics Approach.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2017Article
- Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.Nature genetics · 2017Article
- Epigenetic Reprogramming in Naive CD4+ T Cells Favoring T Cell Activation and Non-Th1 Effector T Cell Immune Response as an Early Event in Lupus Flares.Arthritis & rheumatology (Hoboken, N.J.) · 2016Article
- GenomeRunner web server: regulatory similarity and differences define the functional impact of SNP sets.Bioinformatics (Oxford, England) · 2016Article
- Hypomethylation coordinates antagonistically with hypermethylation in cancer development: a case study of leukemia.Human genomics · 2016Article
- A Whole Methylome CpG-SNP Association Study of Psychosis in Blood and Brain Tissue.Schizophrenia bulletin · 2016Article
- Establishing an analytic pipeline for genome-wide DNA methylation.Clinical epigenetics · 2016Review
- High density methylation QTL analysis in human blood via next-generation sequencing of the methylated genomic DNA fraction.Genome biology · 2015Article
- I-GSEA4GWAS v2: a web server for functional analysis of SNPs in trait-associated pathways identified from genome-wide association study.Protein & cell · 2015Article
- Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes.Epigenetics · 2015Article
- Epigenomic elements enriched in the promoters of autoimmunity susceptibility genes.Epigenetics · 2014Article
- Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren's syndrome.Nature genetics · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationOne of the challenges in interpreting high-throughput genomic studies such as a genome-wide associations, microarray or ChIP-seq is their open-ended nature-once a set of experimentally identified regions is identified as statistically significant, at least two questions arise: (i) besides P-value, do any of these significant regions stand out in terms of biological implications? (ii) Does the set of significant regions, as a whole, have anything in common genome wide? These issues are difficult to address because of the growing number of annotated genomic features (e.g. single nucleotide polymorphisms, transcription factor binding sites, methylation peaks, etc.), and it is difficult to know a priori which features would be most fruitful to analyze. Our goal is to provide partial automation of this process to begin examining associations between experimental features and annotated genomic regions in a hypothesis-free, data-driven manner.
resultsWe created GenomeRunner-a tool for automating annotation and enrichment of genomic features of interest (FOI) with annotated genomic features (GFs), in different organisms. Besides simple association of FOIs with known GFs GenomeRunner tests whether the enriched FOIs, as a group, are statistically associated with a large and growing set of genomic features. AVAILABILITY: GenomeRunner setup files and source code are freely available at http://sourceforge.net/projects/genomerunner. CONTACT: mikhail-dozmorov@omrf.org; Jonathan-Wren@omrf.org; jdwren@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.