miRTarVis is an interactive visual analysis tool for microRNA-mRNA expression profile data.
Daekyoung Jung, Sehi L'Yi, Bohyoung Kim, Robert J. Freishtat, Mamta Giri, Eric Hoffman, and Jinwook Seo / 2015
- Daekyoung Jung, Seoul National University, Seoul, Republic of Korea
- Sehi L'Yi, Seoul National University, Seoul, Republic of Korea
- Bohyoung Kim, Hankuk University of Foreign Studies, Yongin-si, Republic of Korea
- Robert J. Freishtat, Division of Emergency Medicine, Children’s National Medical Center, USA
- Mamta Giri, Center for Genetic Medicine Research, Children’s National Medical Center, USA
- Eric Hoffman, George Washington University, Washington, D.C, USA
- Jinwook Seo, Seoul National University, Seoul, Republic of Korea
- Background: MicroRNAs (miRNA) are short nucleotides that down-regulate its target genes. Various miRNA target prediction algorithms have used sequence complementarity between miRNA and its targets. Recently, other algorithms tried to improve sequence-based miRNA target prediction by exploiting miRNA-mRNA expression profile data. Some web-based tools are also introduced to help researchers predict targets of miRNAs from miRNA-mRNA expression profile data. A demand for a miRNA-mRNA visual analysis tool that features novel miRNA prediction algorithms and more interactive visualization techniques exists.
- Results: We designed and implemented miRTarVis, which is an interactive visual analysis tool that predicts targets of miRNAs from miRNA-mRNA expression profile data and visualizes the resulting miRNA-target interaction network. miRTarVis has intuitive interface design in accordance with the analysis procedure of load, filter, predict, and visualize. It predicts targets of miRNA by adopting Bayesian inference and MINE analyses, as well as conventional correlation and mutual information analyses. It visualizes a resulting miRNA-mRNA network in an interactive Treemap, as well as a conventional node-link diagram. miRTarVis is available at hcil.snu.ac.kr/~rati/miRTarVis/index.html.
- Conclusions: We reported findings from miRNA-mRNA expression profile data of asthma patients using miRTarVis in a case study. miRTarVis helps to predict and understand targets of miRNA from miRNA-mRNA expression profile data.
- Excutable files, sample datasets, and tutorials are available at hcil.snu.ac.kr/~rati/miRTarVis/index.html.
- Java Runtime Environment (JRE) version 7+ (64-bit version is recommended, because 32-bit version JRE has memory limits)
- Any OS that supports JRE 7+
- Minimum screen resolution: 1280 x 720
- This work was partly supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government of MSIP (No. NRF-2014R1A2A2A03006998) and by the Korea government of MEST (No. NRF-2011-0030813). This work was also supported by the Clark Family Foundation (USA) and the National Institutes of Health (3R01 NS29525).
- This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. NRF-2011-0030813).
- Daekyoung Jung, Bohyoung Kim, Robert J. Freishtat, Mamta Giri, Eric Hoffman, and Jinwook Seo, miRTarVis: An interactive visual analysis tool for microRNA-mRNA expression profile data, [PDF], 5th Symposium on Biological Data Visualization (BioVis '15)
- Daekyoung Jung, Sehi L'Yi, Bohyoung Kim, and Jinwook Seo, Interactive Visual Analysis of miRNA Target Prediction Results, [PDF], 2017 IEEE International Conference on Big Data and Smart Computing (BigComp '17)