Biology subjects

Daya, M.

Publications and source records attributed to Daya, M..

5 recordsLinked to original sources

bioRxiv2021

SAIGE-BRUSH: an efficient, user-friendly and low cost cloud implementation for genome-wide association studies

SAIGE-Biobank Re-Usable SAIGE Helper (SAIGE-BRUSH) allows users with little computational expertise to utilize SAIGE for GWAS with parallelization and data collection on biobank data sets. This implementation requires no installation and has additional features not programmed within the original SAIGE framework, such as concurrency, reproducibility, reusability, scalability, association analysis results filtering and output plots. This is all achieved without writing any code from the user. This implementation is currently being utilized by the Biobank at the Colorado Center for Personalized Medicine (CCPM) on Google Cloud but is flexible for a number of architectures available to genetic analysts. Availability: This open source implementation is freely available at https://github.com/tbrunetti/SAIGE-BRUSH and is licensed under the MIT License. Contact: Chris Gignoux at chris.gignoux@cuanschutz.edu & Nick Rafaels at nicholas.rafaels@cuanschutz.edu Supplemental Material: For detailed user documentation, please visit https://saige-brush.readthedocs.io/en/latest/

bioinformatics↗

bioRxiv2019

clustifyr: An R package for automated single-cell RNA sequencing cluster classification

BackgroundIn single-cell RNA sequencing (scRNA-seq) analysis, assignment of likely cell types remains a time-consuming, error-prone, and biased process. Current packages for identity assignment use limited types of reference data, and often have rigid data structure requirements. As such, a more flexible tool, capable of handling multiple types of reference data and data structures, would be beneficial. FindingsTo address difficulties in cluster identity assignment, we developed the clustifyr R package. The package leverages external datasets, including gene expression profiles from scRNA-seq, bulk RNA-seq, microarray expression data, and/or signature gene lists, to assign likely cell types. We benchmark various parameters of a correlation-based approach, and also implement a variety of gene list enrichment methods. By providing tools for exploratory data analysis, we demonstrate the feasibility of a simple and effective data-driven approach for cell type assignment in scRNA-seq cell clusters. Conclusionsclustifyr is a lightweight and effective cell type assignment tool developed for compatibility with various scRNA-seq analysis workflows. clustifyr is publicly available at https://github.com/rnabioco/clustifyr

bioinformatics↗

bioRxiv2019

Loss-of-function genomic variants with impact on liver-related blood traits highlight potential therapeutic targets for cardiovascular disease

Cardiovascular diseases (CVD), and in particular cerebrovascular and ischemic heart diseases, are leading causes of death globally.1 Lowering circulating lipids is an important treatment strategy to reduce risk.2,3 However, some pharmaceutical mechanisms of reducing CVD may increase risk of fatty liver disease or other metabolic disorders.4,5,6 To identify potential novel therapeutic targets, which may reduce risk of CVD without increasing risk of metabolic disease, we focused on the simultaneous evaluation of quantitative traits related to liver function and CVD. Using a combination of low-coverage (5x) whole-genome sequencing and targeted genotyping, deep genotype imputation based on the TOPMed reference panel7, and genome-wide association study (GWAS) meta-analysis, we analyzed 12 liver-related blood traits (including liver enzymes, blood lipids, and markers of iron metabolism) in up to 203,476 people from three population-based cohorts of different ancestries. We identified 88 likely causal protein-altering variants that were associated with one or more liver-related blood traits. We identified several loss-of-function (LoF) variants reducing low-density lipoprotein cholesterol (LDL-C) or risk of CVD without increased risk of liver disease or diabetes, including variants in known lipid genes (e.g. APOB, LPL). A novel LoF variant, ZNF529:p.K405X, was associated with decreased levels of LDL-C (P=1.3x10-8) but demonstrated no association with liver enzymes or non-fasting blood glucose levels. Silencing of ZNF529 in human hepatocytes resulted in upregulation of LDL receptor (LDLR) and increased LDL-C uptake in the cells, suggesting that inhibition of ZNF529 or its gene product could be used for treating hypercholesterolemia and hence reduce the risk of CVD. Taken together, we demonstrate that simultaneous consideration of multiple phenotypes and a focus on rare protein-altering variants may identify promising therapeutic targets.

genomics↗

bioRxiv2019

De novo mutations across 1,465 diverse genomes reveal novel mutational insights and reductions in the Amish founder population.

de novo Mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) program, we directly estimate and analyze DNM counts, rates, and spectra from 1,465 trios across an array of diverse human populations. Using the resulting call set of 86,865 single nucleotide DNMs, we find a significant positive correlation between local recombination rate and local DNM rate, which together can explain up to 35.5% of the genome-wide variation in population level rare genetic variation from 41K unrelated TOPMed samples. While genome-wide heterozygosity does correlate weakly with DNM count, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, interestingly, we do find significantly fewer DNMs in Amish individuals compared with other Europeans, even after accounting for parental age and sequencing center. Specifically, we find significant reductions in the number of T[->]C mutations in the Amish, which seems to underpin their overall reduction in DNMs. Finally, we calculate near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by non-additive genetic effects and/or the environment, and that a less mutagenic environment may be responsible for the reduced DNM rate in the Amish. SignificanceHere we provide one of the largest and most diverse human de novo mutation (DNM) call sets to date, and use it to quantify the genome-wide relationship between local mutation rate and population-level rare genetic variation. While we demonstrate that the human single nucleotide mutation rate is similar across numerous human ancestries and populations, we also discover a reduced mutation rate in the Amish founder population, which shows that mutation rates can shift rapidly. Finally, we find that variation in mutation rates is not heritable, which suggests that the environment may influence mutation rates more significantly than previously realized.

genetics↗

bioRxiv2017

Genome-wide association study of asthma in individuals of African ancestry reveals novel asthma susceptibility loci

BACKGROUNDAsthma is a complex disease with striking disparities across racial and ethnic groups, which may be partly attributable to genetic factors. One of the main goals of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to discover genes conferring risk to asthma in populations of African descent.\n\nMETHODSWe performed a genome-wide meta-analysis of asthma across 11 CAAPA datasets (4,827 asthma cases and 5,397 controls), genotyped on the African Diaspora Power Chip (ADPC) and including existing GWAS array data. The genotype data were imputed up to a whole genome sequence reference panel from n=880 African ancestry individuals for a total of 61,904,576 SNPs. Statistical models appropriate to each study design were used to test for association, and results were combined using the weighted Z-score method. We also used admixture mapping as a complementary approach to identify loci involved in asthma pathogenesis in subjects of African ancestry.\n\nRESULTSSNPs rs787160 and rs17834780 on chromosome 2q22.3 were significantly associated with asthma (p=6.57 x 10-9 and 2.97 x 10-8, respectively). These SNPs lie in the intergenic region between the Rho GTPase Activating Protein 15 (ARHGAP15) and Glycosyltransferase Like Domain Containing 1 (GTDC1) genes. Four low frequency variants on chromosome 1q21.3, which may be involved in the \"atopic march\" and which are not polymorphic in Europeans, also showed evidence for association with asthma (1.18 x10-6 [≤] p [≤] 3.06 x10-6). SNP rs11264909 on chromosome 1q23.1, close to a region previously identified by the EVE asthma meta-analysis as having a putative African ancestry specific effect, only showed differences in counts in subjects homozygous for alleles of African ancestry. Admixture mapping also identified a significantly associated region on chromosome 6q23.2, which includes the Transcription Factor 21 (TCF21) gene, previously shown to be differentially expressed in bronchial tissues of asthmatics and non-asthmatics.\n\nCONCLUSIONSWe have identified a number of novel asthma association signals warranting further investigation.

bioinformatics↗