Single cell ideas
Table of Contents
A collection of various (often incomplete or broken) ideas for single cell analysis plus some related topics.
Expression models
- Normalizing flows for EBPM
- Convolutional VAE for spatial transcriptomic data
- EM algorithm for point-Gamma expression model
- Taylor expansions for single cell transforms
- Deep unsupervised clustering of scRNA-seq data
- Model-based clustering of scRNA-seq data
- An improved voom transform for scRNA-seq data
- Massively Parallel Empirical Bayes Poisson Means
Single cell applications
- Learning the structure of RNA expression variation
- Buffering of RNA expression variation
- Poisson GLMM for differential expression
- Fully unsupervised topic models of scRNA-seq time course data
- Differential variance analysis
- Deconvolution of Montoro et al.
- Alternative approaches to scRNA-seq pseudobulk models
- Single cell QTL mapping via sparse multiple regression
- Cardiac trajectory prediction
- Experimental fine-mapping of QTLs from scRNA-seq data
- Single cell alignment
- Population structure in single cell data
Other applications
General methods development
- VAEs without amortized inference
- Hierarchical PMF
- Logistic regression in the presence of error-prone labels
- Is eQTL analysis robust to removing some data points?
- Empirical Bayes inference for the horseshoe prior
- Sparse Poisson Factor Analysis
- Scaling priors for regression models
- Parallel computation of randomized quantiles
- Noisy topic models
- Mutual nearest neighbors in topic model space
- Empirical Bayes Poisson Matrix Factorization
- Causal mediation analysis
- Two-group grade of membership model
- Weighted low rank approximation
- Multivariate fine mapping