scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles

What is being modeled?

Single cell transcriptomic and epigenomic profiles, data integration, transcriptomic regulatory relationship

Description & purpose of resource

scAI is an unsupervised approach that integrates parallel single-cell transcriptomic and epigenomic profiles, which enables the dissection of cellular heterogeneity within both transcriptomic and epigenomic layers and the understanding of transcriptional regulatory mechanisms.

Spatial scales

cellular

Temporal scales

1 - 103 s

hours

This resource is currently

mature and useful in ongoing research

Has this resource been validated?

Yes

How has the resource been validated?

The tool has been validated on 1) simulated data and 2) prior knowledge of transcription factors.

Link to Resource Credibility Assessment

scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles

Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)

Yes

Which resources?

Data imputation tools, clustering methods, trajectory inference methods, visualization methods.

Key publications (e.g. describing or using resource)

Jin, S., Zhang, L. & Nie, Q. scAI: an unsupervised approach for the integrative analysis of parallel single-cell transcriptomic and epigenomic profiles. Genome Biol 21, 25 (2020). https://doi.org/10.1186/s13059-020-1932-8

DOI link to publication describing this resource

https://doi.org/10.1186/s13059-020-1932-8

Link to resource

Open source software

Collaborators

Qing Nie

PI contact information

qnie@uci.edu

Keywords

Integrative analysis; Simultaneous measurements; Single-cell multiomics; Sparse epigenomic profile