Tamsyn M. Crowley

This paper provides a guide for applying compositional data analysis to NGS count data, emphasizing log-ratio transformations and addressing limitations of conventional normalization methods.

This study identifies sex-dependent and -independent biomarkers in ASD using post-mortem brain RNA-Seq and blood microarray data, highlighting sex-specific gene expression differences and pathway dysregulation.

The paper benchmarks ALDEx2, a log-ratio transformation method, against conventional RNA-Seq differential expression tools, showing it has high precision and comparable performance on real data.

This paper reviews compositional data analysis principles and discusses their application to sequencing data, highlighting challenges and future directions.

The paper introduces an R package for analyzing compositional data by implementing two proportionality measures and discussing their application to genomic data.