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Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns
- Source :
- PLoS Computational Biology, PLoS Computational Biology, Vol 17, Iss 10, p e1009423 (2021)
- Publication Year :
- 2021
-
Abstract
- Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These algorithms take as input epigenomic datasets, such as chromatin immunoprecipitation-sequencing (ChIP-seq) measurements of histone modifications or transcription factor binding. They partition the genome and assign a label to each segment such that positions with the same label exhibit similar patterns of input data. SAGA algorithms discover categories of activity such as promoters, enhancers, or parts of genes without prior knowledge of known genomic elements. In this sense, they generally act in an unsupervised fashion like clustering algorithms, but with the additional simultaneous function of segmenting the genome. Here, we review the common methodological framework that underlies these methods, review variants of and improvements upon this basic framework, and discuss the outlook for future work. This review is intended for those interested in applying SAGA methods and for computational researchers interested in improving upon them.
- Subjects :
- Epigenomics
Computer science
Markov models
Gene Expression
Review
Genome
Cell Signaling
Preprocessor
Segmentation
Hidden Markov models
Biology (General)
Statistical Data
Analysts
Ecology
Chromosome Biology
Statistics
Genome project
Genomics
Chromatin
Histone Code
Physical sciences
Professions
Computational Theory and Mathematics
Modeling and Simulation
Chromatin Immunoprecipitation Sequencing
Epigenetics
Algorithm
Genomic Signal Processing
Algorithms
Protein Binding
Signal Transduction
QH301-705.5
Cellular and Molecular Neuroscience
Genetics
Humans
Cluster analysis
Enhancer
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Biology and Life Sciences
Computational Biology
Molecular Sequence Annotation
Probability theory
Cell Biology
Genome Analysis
Genome Annotation
People and Places
Population Groupings
Mathematics
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- PLoS computational biology
- Accession number :
- edsair.doi.dedup.....a0ac0d91c0a3b27dbb78ccf4e98e2037