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Graphical Operation

The intuitive interactive data browser is essential for understanding.

If you drag on a chart, you'll instantly know what those genes are. Likewise, if you reversely search for gene names or keywords, you'll immediately see how those genes behave on the graph. In such ways, it is much easier to understand the data than to operate with commands. And all views are associated so that you can grab the data from multi-angles.

The omics data is so complex that you must fully use such sophisticated graphical aids because understanding data is fundamental. Unfortunately, many training programs about omics data analysis tend to underestimate viewing data while focusing too much on statistical commanding. However, you have to understand the data adequately first of all.

• Why do you better analyze RNA-Seq Counts than TPM or FPKM?
• Why do you need multi-visualizations, not single ones?
• Why can't you overtrust FPKM or TPM as validly normalized?
• Why can't you overestimate single-cell RNA-Seq results?
• RNA-Seq data quality depends on the input RNA.

Details of each viewer;

Details of Normalization and Pre-processing;

Supporting Various Types of Omics Data

Undoubtedly, it would be a great help if you have a database of your own experimental data with massive omics data sets available from the web like GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas). Indeed, nobody can thoroughly extract biological knowledge from omics data. So the legacy data sets are still juicy.

However, handling data sets in various formats generated by multiple systems might take time, and of course, it requires experience and skills. If it's hard, we can offer Data Analysis Service.

Supporting file formats;

• tab-delimited text files (RNA-Seq count/TPM/FPKM, Microarray signals, DNA methylation ratio, proteomics abundances, etc.)
• RNA-Seq FASTQ files
• BED/WIG/Bigwig files (ChIP-Seq, ATA-Seq, etc.)
• And more.

Details of importing data files;

Details of importing data sets from the web;

If you are still looking for the file type you want to analyze, or if you face errors in importing files, please find solutions on the web or consider charged online training.

Instant And Deep Sharing of Omics Data

Human beings have yet to learn how to interpret omics data. So we absolutely need much more discussion involving biologists, not only bioinformaticians. However, it takes work for them to participate due to the unfriendliness of bioinformatics tools.

If you export the SSA file from Subio Platform, you can hand the raw data with final and intermediate results in a single file. Your collaborators rebuild the analysis environment only by importing the SSA file, and they can instantly start examining analysis results and re-analyzing from their perspectives. It enables deeper discussion and collaboration than PDF- and Excel-based handovers.

• The instant and comprehensive omics data sharing ― Import/Export an SSA file

Small License Fee Enables Sustainability

Although open-source and free software have supported bioinformatics, the problems of such tools also become apparent. For example, operating systems and middleware must keep updated to counter various threats. On the other hand, bioinformaticians abandoned their tools without maintenance, and it caused problems that researchers couldn't use the same software in their long-running studies. This problem happened because bioinformaticians' evaluations are biased toward developing new tools, and there is little incentive to maintain existing tools.

To solve this problem, we established Subio as an autonomously sustainable operating entity that receives a small license fee from plug-in users. Since the advent of microarrays, various measurement devices and analysis software have appeared and disappeared, but Subio has kept running without wavering from its original purpose. As a result, it becomes the only stable software platform to accumulate and integrate new and legacy omics data for analysis.

Subio also proposes to bioinformaticians an alternative distribution of their tools to keep them maintained.

Integrate with Bioinformatics Tools in R or Python

Subio Platform offers valuable utilities and interactive GUI that R or Python don't provide, but conversely, it doesn't offer advanced statistical features. However, you can easily output data from Subio Platform and let R or Python tools take over the statistical tasks.

Subio Platform and bioinformatics tools written in R or Python complement each other rather than compete. By combining them, you can build a comprehensive analysis system at a very reasonable cost.

See the last part of this movie.

• Extracting differentially expressing genes (DEGs) by ANOVA