| 1. |
- Aguet, Francois, et al.
(författare)
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Molecular quantitative trait loci
- 2023
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Ingår i: NATURE REVIEWS METHODS PRIMERS. - : Springer Nature. - 2662-8449. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Understanding functional effects of genetic variants is one of the key challenges in human genetics, as much of disease-associated variation is located in non-coding regions with typically unknown putative gene regulatory effects. One of the most important approaches in this field has been molecular quantitative trait locus (molQTL) mapping, where genetic variation is associated with molecular traits that can be measured at scale, such as gene expression, splicing and chromatin accessibility. The maturity of the field and large-scale studies have produced a rich set of established methods for molQTL analysis, with novel technologies opening up new areas of discovery. In this Primer, we discuss the study design, input data and statistical methods for molQTL mapping and outline the properties of the resulting data as well as popular downstream applications. We review both the limitations and caveats of molQTL mapping as well as future potential approaches to tackle them. With technological development now providing many complementary methods for functional characterization of genetic variants, we anticipate that molQTLs will remain an important part of this toolkit as the only existing approach that can measure human variation in its native genomic, cellular and tissue context.
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| 2. |
- Brown, Brielin C., et al.
(författare)
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Multiset correlation and factor analysis enables exploration of multi-omics data
- 2023
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Ingår i: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:8, s. 100359-
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Tidskriftsartikel (refereegranskat)abstract
- Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.
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| 3. |
- Buschur, Kristina L., et al.
(författare)
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Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis
- 2023
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Ingår i: Respiratory Research. - : Springer Nature. - 1465-9921 .- 1465-993X. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundChronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment.MethodsBlood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples.ResultsThe discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS).ConclusionsThe identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.
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| 4. |
- Buschur, Kristina L., et al.
(författare)
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Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease
- 2024
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Ingår i: Annals of the American Thoracic Society. - : American Thoracic Society. - 2329-6933 .- 2325-6621. ; 21:6, s. 884-894
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Tidskriftsartikel (refereegranskat)abstract
- Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.
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| 5. |
- Einson, Jonah, et al.
(författare)
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Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants
- 2023
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Ingår i: Genetics. - : Oxford University Press (OUP). - 0016-6731 .- 1943-2631. ; 224:4
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Tidskriftsartikel (refereegranskat)abstract
- Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.
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| 6. |
- Einson, Jonah, et al.
(författare)
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The impact of genetically controlled splicing on exon inclusion and protein structure
- 2024
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 19:3 March
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Tidskriftsartikel (refereegranskat)abstract
- Common variants affecting mRNA splicing are typically identified though splicing quantitative trait locus (sQTL) mapping and have been shown to be enriched for GWAS signals by a similar degree to eQTLs. However, the specific splicing changes induced by these variants have been difficult to characterize, making it more complicated to analyze the effect size and direction of sQTLs, and to determine downstream splicing effects on protein structure. In this study, we catalogue sQTLs using exon percent spliced in (PSI) scores as a quantitative phenotype. PSI is an interpretable metric for identifying exon skipping events and has some advantages over other methods for quantifying splicing from short read RNA sequencing. In our set of sQTL variants, we find evidence of selective effects based on splicing effect size and effect direction, as well as exon symmetry. Additionally, we utilize AlphaFold2 to predict changes in protein structure associated with sQTLs overlapping GWAS traits, highlighting a potential new use-case for this technology for interpreting genetic effects on traits and disorders.
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| 7. |
- Flynn, Elise D., et al.
(författare)
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Functional Characterization of Genetic Variant Effects on Expression
- 2022
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Ingår i: Annual Review of Biomedical Data Science. - : Annual Reviews. - 2574-3414. ; 5, s. 119-139
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Tidskriftsartikel (refereegranskat)abstract
- Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression.
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| 8. |
- Flynn, E. D., et al.
(författare)
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Transcription factor regulation of eQTL activity across individuals and tissues
- 2022
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 18:1, s. e1009719-
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Tidskriftsartikel (refereegranskat)abstract
- Tens of thousands of genetic variants associated with gene expression (cis-eQTLs) have been discovered in the human population. These eQTLs are active in various tissues and contexts, but the molecular mechanisms of eQTL variability are poorly understood, hindering our understanding of genetic regulation across biological contexts. Since many eQTLs are believed to act by altering transcription factor (TF) binding affinity, we hypothesized that analyzing eQTL effect size as a function of TF level may allow discovery of mechanisms of eQTL variability. Using GTEx Consortium eQTL data from 49 tissues, we analyzed the interaction between eQTL effect size and TF level across tissues and across individuals within specific tissues and generated a list of 10,098 TF-eQTL interactions across 2,136 genes that are supported by at least two lines of evidence. These TF-eQTLs were enriched for various TF binding measures, supporting with orthogonal evidence that these eQTLs are regulated by the implicated TFs. We also found that our TF-eQTLs tend to overlap genes with gene-by-environment regulatory effects and to colocalize with GWAS loci, implying that our approach can help to elucidate mechanisms of context-specificity and trait associations. Finally, we highlight an interesting example of IKZF1 TF regulation of an APBB1IP gene eQTL that colocalizes with a GWAS signal for blood cell traits. Together, our findings provide candidate TF mechanisms for a large number of eQTLs and offer a generalizable approach for researchers to discover TF regulators of genetic variant effects in additional QTL datasets.
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| 9. |
- George, Sophia H.L., et al.
(författare)
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Increasing diversity of functional genetics studies to advance biological discovery and human health
- 2023
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Ingår i: American Journal of Human Genetics. - : Cell Press. - 0002-9297 .- 1537-6605. ; 110:12, s. 1996-2002
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Forskningsöversikt (refereegranskat)abstract
- In this perspective we discuss the current lack of genetic and environmental diversity in functional genomics datasets. There is a well-described Eurocentric bias in genetic and functional genomic research that has a clear impact on the benefit this research can bring to underrepresented populations. Current research focused on genetic variant-to-function experiments aims to identify molecular QTLs, but the lack of data from genetically diverse individuals has limited analyses to mostly populations of European ancestry. Although some efforts have been established to increase diversity in functional genomic studies, much remains to be done to consistently generate data for underrepresented populations from now on. We discuss the major barriers for this continuity and suggest actionable insights, aiming to empower research and researchers from underserved populations.
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| 10. |
- Glinos, Dafni A., et al.
(författare)
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Transcriptome variation in human tissues revealed by long-read sequencing
- 2022
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 608:7922, s. 353-359
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Tidskriftsartikel (refereegranskat)abstract
- Regulation of transcript structure generates transcript diversity and plays an important role in human disease(1-7). The advent oflong-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure(8-)(16). In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.
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| 11. |
- Kasela, Silva, et al.
(författare)
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Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects
- 2024
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 111:1, s. 133-149
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Tidskriftsartikel (refereegranskat)abstract
- Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
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| 12. |
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| 13. |
- Lappalainen, Tuuli, et al.
(författare)
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From variant to function in human disease genetics
- 2021
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 373:6562, s. 1464-1468
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Forskningsöversikt (refereegranskat)abstract
- Over the next decade, the primary challenge in human genetics will be to understand the biological mechanisms by which genetic variants influence phenotypes, including disease risk. Although the scale of this challenge is daunting, better methods for functional variant interpretation will have transformative consequences for disease diagnosis, risk prediction, and the development of new therapies. An array of new methods for characterizing variant impact at scale, using patient tissue samples as well as in vitro models, are already being applied to dissect variant mechanisms across a range of human cell types and environments. These approaches are also increasingly being deployed in clinical settings. We discuss the rationale, approaches, applications, and future outlook for characterizing the molecular and cellular effects of genetic variants.
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| 14. |
- Lappalainen, Tuuli, et al.
(författare)
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Genetic and molecular architecture of complex traits
- 2024
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Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 187:5, s. 1059-1075
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Forskningsöversikt (refereegranskat)abstract
- Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.
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| 15. |
- Li, Xiaoting, et al.
(författare)
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Identifying genetic regulatory variants that affect transcription factor activity
- 2023
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Ingår i: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:9
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.
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| 16. |
- Martorella, Molly, et al.
(författare)
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Evaluation of noninvasive biospecimens for transcriptome studies
- 2023
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Ingår i: BMC Genomics. - : Springer Nature. - 1471-2164. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Transcriptome studies disentangle functional mechanisms of gene expression regulation and may elucidate the underlying biology of disease processes. However, the types of tissues currently collected typically assay a single post-mortem timepoint or are limited to investigating cell types found in blood. Noninvasive tissues may improve disease-relevant discovery by enabling more complex longitudinal study designs, by capturing different and potentially more applicable cell types, and by increasing sample sizes due to reduced collection costs and possible higher enrollment from vulnerable populations. Here, we develop methods for sampling noninvasive biospecimens, investigate their performance across commercial and in-house library preparations, characterize their biology, and assess the feasibility of using noninvasive tissues in a multitude of transcriptomic applications. We collected buccal swabs, hair follicles, saliva, and urine cell pellets from 19 individuals over three to four timepoints, for a total of 300 unique biological samples, which we then prepared with replicates across three library preparations, for a final tally of 472 transcriptomes. Of the four tissues we studied, we found hair follicles and urine cell pellets to be most promising due to the consistency of sample quality, the cell types and expression profiles we observed, and their performance in disease-relevant applications. This is the first study to thoroughly delineate biological and technical features of noninvasive samples and demonstrate their use in a wide array of transcriptomic and clinical analyses. We anticipate future use of these biospecimens will facilitate discovery and development of clinical applications.
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| 17. |
- Morris, John A., et al.
(författare)
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Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens
- 2023
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 380:6646
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Tidskriftsartikel (refereegranskat)abstract
- Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse, biobank-scale GWAS data, massively parallel CRISPR screens, and single-cell transcriptomic and proteomic sequencing, we discovered 124 cis-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion through base editing, we connected specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively parallel characterization of the target genes and mechanisms of human noncoding variants in both cis and trans.
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| 18. |
- Schmitz, Daniel, 1995-
(författare)
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Beyond GWAS : Novel Methods and Resources for Genetic Epidemiology
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Since the first human genome assembly’s release, our knowledge of the genetic architecture of complex traits and diseases has grown steadily. Genome-wide association studies (GWAS) played a major role but are limited to common traits and single-nucleotide polymorphisms (SNPs). Technologies and resources like next-generation sequencing, Mendelian Randomization (MR), long-read sequencing and improved reference genomes enable the investigation of variants inaccessible to GWAS, such as copy number variations (CNVs), rare variants and variants in previously unresolved regions.In project I, we performed a GWAS of estradiol measurements using data from UK Biobank and quantified estradiol’s effect on bone mineral density (BMD) using MR. 14 loci were associated with estradiol levels in males, of which one was also significant in females and an additional female-specific locus. We found a significant effect of estradiol on BMD, confirming previous research of estrogen’s importance for skeletal health.In project II, we used the GWAS results from project I to investigate the effect of endogenous estradiol on breast, endometrial and ovarian cancer using MR. Estradiol was associated with ovarian cancer and nominally associated with estrogen receptor-positive breast cancer, demonstrating the effect of endogenous estrogen on cancer risk. In project III, we quantified the effect of 184,182 CNVs on 438 blood plasma proteins using whole-genome sequencing (WGS) data from a Northern Swedish cohort and validated our findings using long-read sequencing in a subcohort. 15 CNVs were associated with 16 proteins of which four could be validated using long reads and three more were more complex variation. Our findings show the effects of CNVs on the plasma proteome and highlight the application different sequencing technologies for CNV detection.In project IV, we evaluated the use of T2T-CHM13 as reference for the SweGen cohort. Compared to GRCh38, mapping quality improved and we identified 9.8 million more variants. Sensitivity for rare, singleton and functionally relevant variants was higher. These findings show how research and clinical applications benefit from T2T-CHM13 by improving detection of previously unknown functionally relevant variation.This thesis demonstrates the application of novel technologies and resources in genomics to detect variation and study its impact on quantitative traits. By using genotyping and WGS variants from short and long reads, I showed how we can leverage these technologies for research beyond GWAS.
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| 19. |
- Smolinska Garbulowska, Karolina
(författare)
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Elucidation of complex diseases by machine learning
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Uncovering the interpretability of models for complex health-related problems is a crucial task that is often neglected in machine learning (ML). The amount of available data makes the problem even more complicated. The focal point of my research was building and applying specialized tools that identify relevant descriptors (features and their values). These tools cover a spectrum of methods that originate in ML, statistics and network visualization.In the first part of the thesis, we predicted regulatory elements with potential regulatory impact on gene expression by incorporating several annotations tracks. Then, we created the funMotifs framework that enables the identification and analysis of functional transcription factor (TF) motifs in a tissue-specific manner (Paper I). The TF motifs were described by different chromatin signals from various genomics platforms. Afterwards, the data were merged into a functional score of the motif using logistic regression.Subsequently, funMotifs was used to characterize a map of regulatory mutations and regulatory elements in 37 cancer types from 2,515 samples (Paper II). We were able to identify 5,749 mutated regulatory elements containing 11,962 regulatory mutations. Additionally, we identified several dysregulated cancer-associated genes nearby the mutated elements. Finally, enrichment of cancer-related pathways was observed for the genes linked with the mutated elements.In the second part, we focused on interpretable ML modeling with rule-based classifiers. A rule-based model (RBM) consists of a set of IF-THEN rules, which are legible and allow to determine combinations of descriptors. To analyze RBMs, we created the R.ROSETTA R package that is a wrapper of ROSETTA (Paper III). As a result R.ROSETTA gained several additional functionalities that simplify validation and interpretation of RBMs.Visual inspection of RBMs is an essential step towards the identification of interesting descriptors of a classifier. In order to support the analysis of complex RBMs, we created the VisuNet R tool for rule network (RN) visualization (Paper IV). These networks are constructed from IF-THEN rules that constitute RBM; nodes are descriptors in rules, and an edge connects two nodes if the corresponding descriptors occur in the same rule. By creating RN for RBM, we are able to use network concepts to analyze complex health-related processes. We applied VisuNet on various datasets to illustrate the properties of the tool.In our studies, we showed the importance of identification of relevant descriptors for biological problems. Moreover, our methods may contribute to a better understanding of complex diseases.
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| 20. |
- Uffelmann, E., et al.
(författare)
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Genome-wide association studies
- 2021
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Ingår i: Nature Reviews Methods Primers. - : Springer Nature. - 2662-8449. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase. GWAS results have a range of applications, such as gaining insight into a phenotype’s underlying biology, estimating its heritability, calculating genetic correlations, making clinical risk predictions, informing drug development programmes and inferring potential causal relationships between risk factors and health outcomes. In this Primer, we provide the reader with an introduction to GWAS, explaining their statistical basis and how they are conducted, describe state-of-the art approaches and discuss limitations and challenges, concluding with an overview of the current and future applications for GWAS results.
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