Alevin-fry unlocks rapid, accurate and memory-frugal quantification of single-cell RNA-seq data.

ABSTRACT: The rapid growth of high-throughput single-cell and single-nucleus RNA-sequencing (scRNA-seq and snRNA-seq) technologies has produced a wealth of data over the past few years. The size, volume and distinctive characteristics of these data necessitate the development of new computational methods to accurately and efficiently quantify sc/snRNA-seq data into count matrices that constitute the input to downstream analyses. We introduce the alevin-fry framework for quantifying sc/snRNA-seq data. In addition to being faster and more memory frugal than other accurate quantification approaches, alevin-fry ameliorates the memory scalability and false-positive expression issues that are exhibited by other lightweight tools. We demonstrate how alevin-fry can be effectively used to quantify sc/snRNA-s

SUBMITTER: He D 

PROVIDER: S-EPMC8933848 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature