2017 Fiscal Year Final Research Report
Integration and normalization method for improving the comparative epigenome pipeline
| Project/Area Number |
15K18465
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
System genome science
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Keywords | ChIP-seq法 / Hi-C法 / 大規模解析 / エピゲノム / 品質評価 / ゲノム立体構造 |
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| Outline of Final Research Achievements |
Recent advances in sequencing analyses enable us to compare hundreds of ChIP-seq samples simultaneously; such large-scale analysis has potential to reveal the high-dimensional interrelationship level for regulatory elements and annotate novel functional genomic regions de novo. However, there are various factors that can affect the data quality of the sample preparation step, especially for tissue samples and low-input analyses. It is still difficult to eliminate or normalize biases in each sample. To overcome this problem, we have developed three programs: (i) DROMPA3, cost-effective ChIP-seq pipeline; (ii) SSP, a novel quality assessment tool of ChIP-seq data; and (iii) Hi-C analysis pipeline. These programs can provide us with more robust and effective large-scale epigenome analysis.
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| Free Research Field |
バイオインフォマティクス
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