Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For instance, single-cell RNA sequencing (scRNA-Seq) measures the transcriptome-wide gene expression at a single-cell resolution, allowing for studying the heterogeneity among the cells of the same population and revealing complex and rare cell populations. On the other hand, single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-Seq) can be used to define transcriptional and epigenetic changes by analyzing the chromatin accessibility at the single-cell level. However, the integration of multi-omics data still remains one of the most difficult tasks in bioinformatics. In this chapter, we focus on the combination of scRNA-Seq and scATACSeq data to perform an integrative analysis of the single-cell transcriptome and chromatin accessibility of human fetal progenitors.

(2023). Integration of scATAC-Seq with scRNA-Seq Data . Retrieved from https://hdl.handle.net/10446/236496

Integration of scATAC-Seq with scRNA-Seq Data

Tangherloni, Andrea
2023-01-01

Abstract

Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For instance, single-cell RNA sequencing (scRNA-Seq) measures the transcriptome-wide gene expression at a single-cell resolution, allowing for studying the heterogeneity among the cells of the same population and revealing complex and rare cell populations. On the other hand, single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-Seq) can be used to define transcriptional and epigenetic changes by analyzing the chromatin accessibility at the single-cell level. However, the integration of multi-omics data still remains one of the most difficult tasks in bioinformatics. In this chapter, we focus on the combination of scRNA-Seq and scATACSeq data to perform an integrative analysis of the single-cell transcriptome and chromatin accessibility of human fetal progenitors.
2023
Berest, Ivan; Tangherloni, Andrea
File allegato/i alla scheda:
File Dimensione del file Formato  
Berest&Tangherloni-Integration_scATAC-Seq&scRNA-Seq_Data.pdf

Solo gestori di archivio

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 513.01 kB
Formato Adobe PDF
513.01 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/236496
Citazioni
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact