Eduardo da Veiga Beltrame

A hyperparameter benchmark of VAE-based methods for scRNA-seq batch integration

This study benchmarks VAE-based methods for scRNA-seq batch integration, finding dataset-dependent performance trade-offs and recommending hyperparameter settings for optimal results.

Single-nucleus resolution mapping of the adult C. elegans and its application to elucidate inter- and trans-generational response to alcohol.

This study uses single-nucleus RNA-seq to map the adult C. elegans transcriptome and assess inter- and trans-generational effects of alcohol exposure at cell type resolution.

scvi-tools: a library for deep probabilistic analysis of single-cell omics data

scvi-tools provides a Python package for probabilistic analysis of single-cell omics data, offering standardized interfaces and extensible tools for various analysis tasks.

Single cell tools for WormBase

The paper introduces two web apps for analyzing single-cell RNA sequencing data with C. elegans datasets from WormBase.

Modular and efficient pre-processing of single-cell RNA-seq

The paper presents a modular and efficient workflow for single-cell RNA-seq pre-processing using kallisto and bustools, demonstrating its flexibility for RNA velocity analyses.

Deletion of Stk11 and Fos in BLA projection neurons alters their intrinsic excitability and impairs formation of long-term aversive memory

A curated database reveals trends in single-cell transcriptomics

The paper curates a database of single-cell transcriptomics studies to analyze trends in the field and provides insights into cell type identification.

Quantifying the tradeoff between sequencing depth and cell number in single-cell RNA-seq

The paper quantifies the tradeoff between sequencing depth and cell number in single-cell RNA-seq, finding that deeper sequencing per cell provides greater benefits than increasing cell numbers beyond 15,000 reads per cell.