Masakari: visualization supported statistical analysis of genome segmentations.
Cell development
ChIP-seq
Chromatin state
Histone modifications
Journal
BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194
Informations de publication
Date de publication:
07 Oct 2020
07 Oct 2020
Historique:
received:
13
09
2019
accepted:
17
09
2020
entrez:
8
10
2020
pubmed:
9
10
2020
medline:
3
11
2020
Statut:
epublish
Résumé
In epigenetics, the change of the combination of histone modifications at the same genomic location during cell differentiation is of great interest for understanding the function of these modifications and their combinations. Besides analyzing them locally for individual genomic locations or globally using correlations between different cells types, intermediate level analyses of these changes are of interest. More specifically, the different distributions of these combinations for different cell types, respectively, are compared to gain new insights. We propose a new tool called 'Masakari' that allows segmenting genomes based on lists of ranges having a certain property, e.g., peaks describing histone modifications. It provides a graphical user interface allowing to select all data sets and setting all parameters needed for the segmentation process. Moreover, the graphical user interface provides statistical graphics allowing to assess the quality and suitability of the segmentation and the selected data. Masakari provides statistics based visualizations and thus fosters insights into the combination of histone modification marks on genome ranges, and the differences of the distribution of these combinations between different cell types.
Sections du résumé
BACKGROUND
BACKGROUND
In epigenetics, the change of the combination of histone modifications at the same genomic location during cell differentiation is of great interest for understanding the function of these modifications and their combinations. Besides analyzing them locally for individual genomic locations or globally using correlations between different cells types, intermediate level analyses of these changes are of interest. More specifically, the different distributions of these combinations for different cell types, respectively, are compared to gain new insights.
RESULTS AND DISCUSSION
CONCLUSIONS
We propose a new tool called 'Masakari' that allows segmenting genomes based on lists of ranges having a certain property, e.g., peaks describing histone modifications. It provides a graphical user interface allowing to select all data sets and setting all parameters needed for the segmentation process. Moreover, the graphical user interface provides statistical graphics allowing to assess the quality and suitability of the segmentation and the selected data.
CONCLUSION
CONCLUSIONS
Masakari provides statistics based visualizations and thus fosters insights into the combination of histone modification marks on genome ranges, and the differences of the distribution of these combinations between different cell types.
Identifiants
pubmed: 33028199
doi: 10.1186/s12859-020-03761-6
pii: 10.1186/s12859-020-03761-6
pmc: PMC7542120
doi:
Substances chimiques
Chromatin
0
Histones
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
437Subventions
Organisme : DFG
ID : DFG grant 0316165C
Organisme : BMBF
ID : BMBF grant 01KU1002J
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