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MHiC, an integrated user-friendly tool for the identification and visualization of significant interactions in Hi-C data

BACKGROUND: Hi-C is a molecular biology technique to understand the genome spatial structure. However, data obtained from Hi-C experiments is biased. Therefore, several methods have been developed to model Hi-C data and identify significant interactions. Each method receives its own Hi-C data struct...

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Detalles Bibliográficos
Autores principales: Khakmardan, Saman, Rezvani, Mohsen, Pouyan, Ali Akbar, Fateh, Mansoor, Alinejad-Rokny, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068949/
https://www.ncbi.nlm.nih.gov/pubmed/32164554
http://dx.doi.org/10.1186/s12864-020-6636-7
Descripción
Sumario:BACKGROUND: Hi-C is a molecular biology technique to understand the genome spatial structure. However, data obtained from Hi-C experiments is biased. Therefore, several methods have been developed to model Hi-C data and identify significant interactions. Each method receives its own Hi-C data structure and only work on specific operating systems. RESULTS: We introduce MHiC (Multi-function Hi-C data analysis tool), a tool to identify and visualize statistically signifiant interactions from Hi-C data. The MHiC tool (i) works on different operating systems, (ii) accepts various Hi-C data structures from different Hi-C analysis tools such as HiCUP or HiC-Pro, (iii) identify significant Hi-C interactions with GOTHiC, HiCNorm and Fit-Hi-C methods and (iv) visualizes interactions in Arc or Heatmap diagram. MHiC is an open-source tool which is freely available for download on https://github.com/MHi-C. CONCLUSIONS: MHiC is an integrated tool for the analysis of high-throughput chromosome conformation capture (Hi-C) data.