Statistical and machine learning methods for spatially resolved transcriptomics data analysis
The recent advancement in spatial transcriptomics technology has enabled multiplexed
profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the …
profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the …
A generalized linear mixed model association tool for biobank-scale data
Compared with linear mixed model-based genome-wide association (GWA) methods,
generalized linear mixed model (GLMM)-based methods have better statistical properties …
generalized linear mixed model (GLMM)-based methods have better statistical properties …
[HTML][HTML] Statistical and machine learning methods for spatially resolved transcriptomics with histology
Recent developments in spatially resolved transcriptomics (SRT) technologies have
enabled scientists to get an integrated understanding of cells in their morphological context …
enabled scientists to get an integrated understanding of cells in their morphological context …
Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies
Identifying genes that display spatial expression patterns in spatially resolved transcriptomic
studies is an important first step toward characterizing the spatial transcriptomic landscape …
studies is an important first step toward characterizing the spatial transcriptomic landscape …
Rare coding variant analysis for human diseases across biobanks and ancestries
Large-scale sequencing has enabled unparalleled opportunities to investigate the role of
rare coding variation in human phenotypic variability. Here, we present a pan-ancestry …
rare coding variation in human phenotypic variability. Here, we present a pan-ancestry …
Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale
Large-scale whole-genome sequencing studies have enabled the analysis of rare variants
(RVs) associated with complex phenotypes. Commonly used RV association tests have …
(RVs) associated with complex phenotypes. Commonly used RV association tests have …
SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies
Spatial transcriptomic studies are becoming increasingly common and large, posing
important statistical and computational challenges for many analytic tasks. Here, we present …
important statistical and computational challenges for many analytic tasks. Here, we present …
SAIGE-GENE+ improves the efficiency and accuracy of set-based rare variant association tests
Several biobanks, including UK Biobank (UKBB), are generating large-scale sequencing
data. An existing method, SAIGE-GENE, performs well when testing variants with minor …
data. An existing method, SAIGE-GENE, performs well when testing variants with minor …
Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies
Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies
provides an attractive solution to the problem of collecting large sample sizes for discovering …
provides an attractive solution to the problem of collecting large sample sizes for discovering …
Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies
Quantitative traits analyzed in Genome-Wide Association Studies (GWAS) are often
nonnormally distributed. For such traits, association tests based on standard linear …
nonnormally distributed. For such traits, association tests based on standard linear …