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scaDA: A novel statistical method for differential analysis of single-cell chromatin accessibility sequencing data.
Zhao, Fengdi; Ma, Xin; Yao, Bing; Lu, Qing; Chen, Li.
Afiliación
  • Zhao F; Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America.
  • Ma X; Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America.
  • Yao B; Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America.
  • Lu Q; Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America.
  • Chen L; Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America.
PLoS Comput Biol ; 20(8): e1011854, 2024 Aug.
Article en En | MEDLINE | ID: mdl-39093856
ABSTRACT
Single-cell ATAC-seq sequencing data (scATAC-seq) has been widely used to investigate chromatin accessibility on the single-cell level. One important application of scATAC-seq data analysis is differential chromatin accessibility (DA) analysis. However, the data characteristics of scATAC-seq such as excessive zeros and large variability of chromatin accessibility across cells impose a unique challenge for DA analysis. Existing statistical methods focus on detecting the mean difference of the chromatin accessible regions while overlooking the distribution difference. Motivated by real data exploration that distribution difference exists among cell types, we introduce a novel composite statistical test named "scaDA", which is based on zero-inflated negative binomial model (ZINB), for performing differential distribution analysis of chromatin accessibility by jointly testing the abundance, prevalence and dispersion simultaneously. Benefiting from both dispersion shrinkage and iterative refinement of mean and prevalence parameter estimates, scaDA demonstrates its superiority to both ZINB-based likelihood ratio tests and published methods by achieving the highest power and best FDR control in a comprehensive simulation study. In addition to demonstrating the highest power in three real sc-multiome data analyses, scaDA successfully identifies differentially accessible regions in microglia from sc-multiome data for an Alzheimer's disease (AD) study that are most enriched in GO terms related to neurogenesis and the clinical phenotype of AD, and AD-associated GWAS SNPs.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cromatina / Análisis de la Célula Individual Límite: Animals / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cromatina / Análisis de la Célula Individual Límite: Animals / Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos