OmicsSuite: a customized and pipelined suite for analysis and visualization of multi-omics big data

Abstract

With the advancements in high-throughput sequencing technologies such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass spectrometry, large volumes of biological data in multiple formats can now be obtained through multi-omics analysis. Bioinformatics is constantly evolving and seeking breakthroughs to solve multi-omics problems; however, it is challenging for most experimental biologists to analyse data using command-line interfaces, coding, and scripting. Based on experience with multi-omics, we have developed OmicsSuite, a desktop suite that comprehensively integrates statistics and multi-omics analysis and visualization. The suite has 175 sub-applications in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics, Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell, and Table Operation. We created the user interface with Sequence View, Table View, and intelligent components based on JavaFX and the popular Shiny framework. The multi-omics analysis functions were developed based on BioJava and 300+ packages provided by the R CRAN and Bioconductor communities, and it encompasses over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5 formats, and the programs emphasize data transfer directions and pipeline analysis functions. OmicsSuite can produce pre-publication images and tables, allowing users to focus on biological aspects. OmicsSuite offers multi-omics step-by-step workflows that can be easily applied to horticultural plant breeding and molecular mechanism studies in plants. It enables researchers to freely explore the molecular information contained in multi-omics big data (Source: https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).

Acknowledgements

We thank the CRAN and Bioconductor communities for providing excellent R packages, as well as the developers of R packages used in OmicsSuite. Thanks to Jianming Zeng from University of Macau for his key suggestions in the development process. This work was supported by grants from National Natural Science Foundation of China (32102775), Hainan Province Science and Technology Special Fund (ZDYF2022XDNY234), Earmarked Fund for CARS (No. CARS-49) and Fundamental Research Funds for the Central Universities (2072022). Thanks for the support from the Germplasm resources sharing platform of aquatic species in Fujian Province, XMU-MRB abalone research center.

Authors’ contributions

B.B.M. and W.W.Y. conceived and designed the project. C.H.K., W.W.Y., X.L., and Z.F.H. provided support and development suggestions for the project. B.B.M. and W.D. wrote the Java, R, Shiny, JavaScript codes for OmicsSuite framework and sub-applications. B.B.M. and Y.X.G. designed the user interface layout and interactive animation. B.B.M. prepared the figures and tables and wrote the manuscript. W.W.Y. reviewed and revised the manuscript. All authors read and approved the final manuscript.

Data availability

OmicsSuite projects source on GitHub: https://github.com/OmicsSuite/, version release repository: https://github.com/OmicsSuite/OmicsSuite.github.io/, website: https://omicssuite.github.io, R script source codes repository: https://github.com/OmicsSuite/Rscripts/, example datasets repository: https://github.com/OmicsSuite/Datasets/.

Conflict of interest statement

All authors declare no conflict of interest.

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