Subio’s data analysis service allows you to request low-cost analysis of RNA-Seq data you have already obtained, without including RNA extraction, library preparation, or sequencing. After reviewing the characteristics of the data and the objectives of the analysis, we determine appropriate preprocessing and normalization conditions and provide analyses including PCA, clustering, identification of differentially expressed genes (DEGs), and enrichment analysis such as Gene Ontology (GO) and pathway analysis.
While many data analysis services charge per sample, Subio charges per dataset. As a result, even datasets containing multiple samples can often be analyzed for 198 USD or 198 EUR per dataset. For Plug-in Set users, the price is 119 USD or 119 EUR per dataset. This makes reliable data analysis available at an affordable price. For details, please see the price list.
We accept FASTQ files, as well as text or Excel files containing Gene Counts, TPM, FPKM, or other expression values. We also support other types of omics data, including microarray data.
The service can be used to:
analyze data generated by another company or core facility,
reanalyze previously analyzed data,
assess measurement systems being considered for future experiments,
and provide a second opinion on existing analysis results.
Our data analysis service does not end with the delivery of a PDF report or Excel files. We support researchers in reviewing and reanalyzing their own data, so that they can deepen the biological interpretation of their results.
RNA-Seq data analysis involves steps such as preprocessing, normalization, statistical analysis, and interpretation, but some stages can be outsourced while others should remain with the researcher.
Subio handles preprocessing and core analyses, allowing researchers to focus on validation, interpretation, and discovery.
In many RNA-Seq analysis services, results are delivered as static reports in PDF or Excel format.
As a result:
These challenges can arise in some data analysis outsourcing services.
In particular, caution is needed when experimental services and data analysis services are offered as a combined package. In services that handle everything from the experiment to the analysis as a single workflow, analysis is often performed according to a predefined standard protocol in order to process large numbers of samples efficiently.
However, the state of RNA-Seq data can vary greatly depending on factors such as sample quality, library preparation, read depth, variability between groups, and batch effects. Therefore, even when results are generated according to a standard protocol, dataset-specific biases or potential problems are not necessarily examined in detail.
When the same organization is responsible for both the experiment and the analysis, the analysis workflow may be standardized, while additional investigation of dataset-specific issues or batch effects may not be performed sufficiently before the results are summarized. This is not limited to any particular company or facility. It is a structural challenge that can occur in outsourced analysis services and shared research facilities that need to process large volumes of data efficiently.
For this reason, from a risk management perspective, it is important not simply to accept delivered analysis results as they are, but to be able to review the state of the data and the analysis results, when necessary, from a perspective independent of the experimental service provider.
Subio's data analysis service is also suitable for this kind of second-opinion use. Rather than mechanically applying a standard protocol, we first examine the characteristics and potential biases of each dataset, then select analysis methods according to the state of the data. Because we can review the data from a position independent of the experimental service provider, we can also point out potential issues from a neutral perspective when problems are found in the data. In addition, instead of providing only static reports in PDF or Excel format, we deliver analysis results in a form that allows researchers to review the results themselves and re-examine them under different conditions.
Subio delivers your data in SSA (Subio Series Archive) format, which includes the full analysis process.
By importing the data into Subio Platform, you can:
This is not a fixed "analysis result," but a living dataset that allows continuous validation and exploration.
For example, you can:
Some advanced analyses and visualizations require plugins.
A quick 90-second guide to start validation and additional analyses using your delivered data.
Subio supports a wide range of omics data, including:
We support re-analysis of public datasets such as GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas). We also provide re-analysis of previously generated microarray data, as well as comparative analysis with newly generated RNA-Seq data.
Our service does not end with data delivery.
After delivery, we provide an online session to walk you through your analysis:
All explained visually within Subio Platform.
After delivery, you can access:
with no limit on usage.
Data analysis is not something you fully understand in one pass. We support you continuously as your research progresses.
By using Subio Platform Plug-ins, you can explore your data with greater flexibility through iterative analysis. You can view details of available analysis tools included in each plug-in here.
For those who want to deepen their analysis further, we offer the following benefits. You can also leverage publicly available datasets from other researchers to validate and strengthen your own hypotheses.
(Valid for one year from purchase, with unlimited use)
Not required for RNA-Seq. For microarrays, only the array name is needed.
Please provide tab-delimited text files. If your data is in a different format or you are unsure what to submit, feel free to contact us.
Get a Free Consultation via Email
Prepare a table mapping sample names to experimental parameters, along with any instructions, requirements, or design details.
Compress items 1–3 into a ZIP file and send it via the contact form.
We will provide a quotation. Once approved, please submit your order via the order form.
| Price | Special Price for Plug-in Set User *3 |
|
|---|---|---|
| Small Dataset *1 *2 | 198 USD | 119 USD |
| Large Dataset | 498 USD | 299 USD |
| Price | Special Price for Plug-in Set User *3 |
|
|---|---|---|
| Small Dataset *1 *2 | 198 EUR | 119 EUR |
| Large Dataset | 498 EUR | 299 EUR |
| Price | Special Price for Plug-in Set User *3 |
|
|---|---|---|
| Small Dataset *1 *2 | 20,000 JPY | 12,000 JPY |
| Large Dataset | 50,000 JPY | 30,000 JPY |
| Price | |
|---|---|
| PDF Report Option *4 | 200 USD |
| Express Option *5 | 50% of the total amount |
| Price | |
|---|---|
| PDF Report Option *4 | 200 EUR |
| Express Option *5 | 50% of the total amount |
| Price | |
|---|---|
| PDF Report Option *4 | 20,000 JPY |
| Express Option *5 | 50% of the total amount |
A "Small Dataset" is defined as <100,000 rows and <100 samples. Larger datasets are considered "Large Datasets."
Examples: GSE106602 (70 samples) → Small dataset, GSE234354 (295 samples) → Large dataset.
* For a year from purchasing Plug-in Set.
We accept FASTQ files as input with an additional charge, which depends on the sum of sizes of the FASTQ files, and the formula is one Small Dataset /5GB. We take only one side of FASTQ files for paired-end samples.
* For a year from purchasing Plug-in Set.
We explain about the data and analysis steps in a web meeting. But if you want to keep the information as a file, you can add this option.
We usually deliver the results within two weeks, but the delivery date is not guaranteed. If you need to specify the delivery date, please order "express option" as well. We will deliver the results by 16:00 of the specified date.
A "Small Dataset" is defined as <100,000 rows and <100 samples. Larger datasets are considered "Large Datasets."
Examples: GSE106602 (70 samples) → Small dataset, GSE234354 (295 samples) → Large dataset.
* For a year from purchasing Plug-in Set.
We accept FASTQ files as input with an additional charge, which depends on the sum of sizes of the FASTQ files, and the formula is one Small Dataset /5GB. We take only one side of FASTQ files for paired-end samples.
* For a year from purchasing Plug-in Set.
We explain about the data and analysis steps in a web meeting. But if you want to keep the information as a file, you can add this option.
We usually deliver the results within two weeks, but the delivery date is not guaranteed. If you need to specify the delivery date, please order "express option" as well. We will deliver the results by 16:00 of the specified date.
A "Small Dataset" is defined as <100,000 rows and <100 samples. Larger datasets are considered "Large Datasets."
Examples: GSE106602 (70 samples) → Small dataset, GSE234354 (295 samples) → Large dataset.
* For a year from purchasing Plug-in Set.
We accept FASTQ files as input with an additional charge, which depends on the sum of sizes of the FASTQ files, and the formula is one Small Dataset /5GB. We take only one side of FASTQ files for paired-end samples.
* For a year from purchasing Plug-in Set.
We explain about the data and analysis steps in a web meeting. But if you want to keep the information as a file, you can add this option.
We usually deliver the results within two weeks, but the delivery date is not guaranteed. If you need to specify the delivery date, please order "express option" as well. We will deliver the results by 16:00 of the specified date.
If you already have Gene Counts data, you can simply provide those files. If you only have FASTQ files, we can handle the analysis from preprocessing.
We perform preprocessing, normalization, filtering, and basic statistical analysis before delivery, allowing researchers to focus on validating results and interpreting the biological meaning.
We also offer second-opinion support for already analyzed datasets.
Yes. We can perform the analysis if you provide the GSE number.
Absolutely. We provide continuous support after delivery.
Start by exploring what can be done with your data. If you share your dataset or provide a GSE number, we will propose an appropriate analysis strategy.
Even a short consultation can help clarify your direction. You are also welcome to reach out at the experimental design stage—for example, to discuss whether your planned approach aligns with your research objectives.