Iterative correction of Hi-C data reveals hallmarks of chromosome organization.
Nat Methods
; 9(10): 999-1003, 2012 Oct.
Article
in En
| MEDLINE
| ID: mdl-22941365
ABSTRACT
Extracting biologically meaningful information from chromosomal interactions obtained with genome-wide chromosome conformation capture (3C) analyses requires the elimination of systematic biases. We present a computational pipeline that integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. We validate this ICE (iterative correction and eigenvector decomposition) technique on published data obtained by the high-throughput 3C method Hi-C, and we demonstrate that eigenvector decomposition of the obtained maps provides insights into local chromatin states, global patterns of chromosomal interactions, and the conserved organization of human and mouse chromosomes.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Chromosome Mapping
/
Chromosomes, Human
/
High-Throughput Screening Assays
/
Nucleic Acid Conformation
Limits:
Humans
Language:
En
Journal:
Nat Methods
Journal subject:
TECNICAS E PROCEDIMENTOS DE LABORATORIO
Year:
2012
Document type:
Article
Affiliation country:
United States
Publication country:
EEUU
/
ESTADOS UNIDOS
/
ESTADOS UNIDOS DA AMERICA
/
EUA
/
UNITED STATES
/
UNITED STATES OF AMERICA
/
US
/
USA