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HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ahn, Hongryul | - |
dc.contributor.author | Jung, Inuk | - |
dc.contributor.author | Chae, Heejoon | - |
dc.contributor.author | Kang, Dongwon | - |
dc.contributor.author | Jung, Woosuk | - |
dc.contributor.author | Kim, Sun | - |
dc.date.accessioned | 2020-03-25T04:38:52Z | - |
dc.date.available | 2020-04-05T13:40:37Z | - |
dc.date.issued | 2019-12-02 | - |
dc.identifier.citation | BMC Bioinformatics, (Suppl 16):588 | ko_KR |
dc.identifier.issn | 1471-2105 | - |
dc.identifier.uri | 10.1186/s12859-019-3072-2 | - |
dc.identifier.uri | https://hdl.handle.net/10371/164770 | - |
dc.description.abstract | Background
Integrated analysis that uses multiple sample gene expression data measured under the same stress can detect stress response genes more accurately than analysis of individual sample data. However, the integrated analysis is challenging since experimental conditions (strength of stress and the number of time points) are heterogeneous across multiple samples. Results HTRgene is a computational method to perform the integrated analysis of multiple heterogeneous time-series data measured under the same stress condition. The goal of HTRgene is to identify response order preserving DEGs that are defined as genes not only which are differentially expressed but also whose response order is preserved across multiple samples. The utility of HTRgene was demonstrated using 28 and 24 time-series sample gene expression data measured under cold and heat stress in Arabidopsis. HTRgene analysis successfully reproduced known biological mechanisms of cold and heat stress in Arabidopsis. Also, HTRgene showed higher accuracy in detecting the documented stress response genes than existing tools. Conclusions HTRgene, a method to find the ordering of response time of genes that are commonly observed among multiple time-series samples, successfully integrated multiple heterogeneous time-series gene expression datasets. It can be applied to many research problems related to the integration of time series data analysis. | ko_KR |
dc.description.sponsorship | This work, including publication costs, was supported by National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT (No.NRF-2017M3C4A7065887). This work was also supported by the Collaborative Genome Program for Fostering New Post-Genome Industry of the National Research Foundation (NRF) funded by the Ministry of Science and ICT (MSIT) (No. NRF-2014M3C9A3063541), and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number:
HI15C3224). This work was supported for W.J. by the Agenda program (No.PJ012465032019), Rural Development of dministration of Republic of Korea. | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BMC | ko_KR |
dc.subject | Integration analysis | - |
dc.subject | Multiple time-series gene expression data | - |
dc.subject | Stress response | - |
dc.subject | Response order preserving DEG | - |
dc.title | HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 안홍렬 | - |
dc.contributor.AlternativeAuthor | 정인욱 | - |
dc.contributor.AlternativeAuthor | 채희준 | - |
dc.contributor.AlternativeAuthor | 강동원 | - |
dc.contributor.AlternativeAuthor | 정우석 | - |
dc.contributor.AlternativeAuthor | 김선 | - |
dc.citation.journaltitle | BMC Bioinformatics | ko_KR |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s) | - |
dc.date.updated | 2019-12-08T04:13:06Z | - |
dc.citation.number | Suppl 16 | ko_KR |
dc.citation.startpage | 588 | ko_KR |
dc.citation.volume | 20 | ko_KR |
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