Correcting signal biases and detecting regulatory elements in STARR-seq data.
Genome Res
; 31(5): 877-889, 2021 05.
Article
em En
| MEDLINE
| ID: mdl-33722938
ABSTRACT
High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Genoma Humano
/
Elementos Facilitadores Genéticos
Limite:
Humans
Idioma:
En
Revista:
Genome Res
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos