University College Cork, Lab Researcher
Dr. John Mac Sharry
It is an excellent user interface and the tutorials are brilliant.
You got lost in an unfamiliar town, you met a man who kindly showed the way.
You said "Thank you!" and followed the direction, but you couldn't find it.
You might wonder if he really knew it.
This is what is happening in the omics data analysis. Textbooks describe the steps in detail though, the output is not what you want exactly.
What the hell is going on?
If you are looking for software for the following purposes, you can choose any software like GeneSpring, Partek, Qlucore, R/Bioconductor, etc. You can do it somehow.
But if you think like below, Subio Platform is the solution.
You can overview the workflow of omics data analysis on Analysis Guide. Black rectangles represent what you can do with Subio Platform. You might think of only statistical methods though, the heart of data analysis is to understand the characteristics of data and to interpret it on the biological context. So Data Browsing is the most important part.
You might think that the free version has the significant limitation. But the truth is that Plug-ins are not essential for the data analysis. The professional viewers of Subio Platform allow your deep understanding about the data just by drag & drop. You can explore deeper and extract more biological insights than using R or Excel.
|What you can do on Subio Platform without plug-ins||Detail|
|Scatter Plot (Measurement) View||Detail|
|Line Graph View||Detail|
|Scatter Plot (Samples) View||Detail|
Many software boasting "user friendly" have the automation which apply some routines of normalization and pre-processing on the data. But the truth is that omics data are not uniform and such automation does not work very well. The following analysis of the oddly processed data becomes terrible consequently. The processing with R/Bioconductor has the same problem. We think you should not use automation for normalization at least until it evolves smart enough.
So what should (or can) the analysis software do? We think it is to support analysts' decision makings by the visual aid. So Subio Platform presents the raw data distribution patterns, and how it is changed when a process is applied. Users can go through trials and errors or discuss with somebody to select the right way.
We agree that this task is hard for beginners. But they get to learn the limitation of the data through it, and it leads their correctly interpreting analysis results. So we decided not to make software having automatic normalization, but to provide service that users can consult to experienced stuffs for free. We support researchers who really want to understand their data.
|Finding a proper sequence of normalization and pre-processing.||Detail|
|How to apply the paired T-test?||Detail|
|How to Use Fill Missing Values Block||Detail|
What is interesting in omics data is you already measured genes on which you do not pay attention. Biological information or knowledge is tremendously increasing and what you can extract from the data now will not be the same in the future. You cannot fully squeeze at a time. Why don't you put the data in your tool box for future use? You cannot make fully use of the omics data with R or Excel.
You know that new technologies are being developed rapidly. One type of omics data tells you only one aspect of the super-complicated living system. So you will need to combine the old and new omics data to guess what is really happening in the living system. Subio Platform is technology-neutral and it can handle any quantitative data conveying biological information. You can store variety types of omics data generated over time and integratively analyze them with Subio Platform.
By the way, tons of omics data sets are available via internet. Subio Platform support semi-automatic import data from GEO or GDC databases. Those data have been already analyzed by someone, but nobody has extracted all knowledge from the data yet. If you keep such data in your Subio Platform as the reference, your tool box becomes more powerful.
|Importing An Excel Data||Detail|
|Importing RNA-Seq Data (A Table of Counts or FPKMs or RPKMs)||Detail|
|Importing Agilent Microarray Data||Detail|
|Importing Affymetrix GeneChip Data||Detail|
|Importing and analyzing public expression data sets from GEO.||Detail|
|Importing TCGA RNA-Seq data||Detail|
|Importing TCGA miRNA-Seq data||Detail|
|Importing and analyzing TCGA methylation data||Detail|
Let's think you ask somebody to analyze data. You know that the real biological experiment is far from the perfect. So you, who know very well about the experimental design and assumptions, are needed to be involved in the decision makings during the data analysis. But you are not often invited to the discussion and just receive Excel and PDF files as result. The reality is that analysis workflow is a black box, and you don't know how the decisions were eventually made.
Of course, you have not only the final results but also the raw data. It is not common that you ask analyzing the data to other analysts to compare, or get second opinions from the third party. Consequently, to have raw data never guarantees the quality of data analysis practically.
So we developed implemented a data sharing format named SSA file, which can contains all information about the data set like raw data files, gene annotation and biological information, parameters and experimental information, final and intermediate results, data of associated experiments, reference papers, etc. You can easily import the SSA file into Subio Platform by drag & drop. It allows you and other researchers checking the quality of data itself and analysis steps.
Additionally, you and collaborators can take over the analysis with Subio Platform of their own. Many people's eyes with different knowledge, skills or backgrounds drastically increase the chance of discovery than an individual perspective. Letting all members be involved in analyzing and discussing is the best education on omics. It will nurture the significant strength of the team in the future. The active data sharing is the long-term strategy.
|The deep sharing of omics data by SSA file.||Detail|
You cannot launch or login to commercial data analysis software like GeneSpring after a license expires. You have to keep paying to access to your own data. This is the obstacle for turning data to assets, sharing data and having open discussions.
We sell plug-in licenses and you can buy them for specific computers and periods. The big difference from other commercial tools is you still can see all the data even after a license expires, including analysis results which were created with plug-in tools. And we show above that you can continue intrinsically analyzing data without plug-ins. So do members who are received SSA files. Not all members must buy plug-in licenses. Most of them can join the analysis and discussions without plug-ins.
This is what is the most important, because it will gradually bring the following changes to your team.
We think such a deep co-working environment is the fundament of new life science which is one of the most challenging frontiers for human beings.
Almost no researchers know Subio Platform, comparing to Excel, R and GeneSpring. You might worry about using such unknown software.
Subio set the policy that we do not spend money on sales or marketing, but on development and user support. We do not hire sales person, we do not appear at trade shows or on media.
By avoiding spending our time and money on such things, we have been focusing on the development and improvement of Subio Platform. We have listened to users' feedbacks and implemented suggested idea. We are proud of the achievement of supreme usability as a result.
Even though Subio Platform is not very popular, you can use the output for publications. If you get comments from referees, our technical support helps your reasonable justifying or logical modifications. It is used by many users for 10 years, and there are a good number of publications citing our software.
The design policy of Subio Platform is that wet biologists can use it easily. So we select statistical functions very carefully.
Although "Highly sophisticated" statistical methods actually have strict restrictions in applicable conditions or assumptions, users tend to ignore them and wrongly use them. You know how much p-values are abused in the biological society. So we selected only general methods which can relatively widely be applicable.
And we eliminated methods which became nonsense in the history of the microarray data analysis. For example, z-score normalization was sometimes necessary due to the terrible quality of spotted dual channel microarrays. But it lost the value as microarray technologies mature. It became rather harmful because it cancels the difference of variance which is one of important biological information.
Any methods have advantages and disadvantages, and the balance changes according to data characteristics. So it is dangerous to mimic a way of a textbook or paper. What we think most important is that users can choose right methods to the data case by case. So we carefully eliminated methods even if they were often used in papers or textbook, rather than putting methods as many as possible.
But we know sometimes you need those functions which we eliminated from Subio Platform. So you can work with both Subio Platform and R/Bioconductor together. Subio Platform with interactive viewers and R with comprehensive collection of statistical methods are the most powerful combination. If you cannot make R scripts, please consider our software development service.
By the way, you might use commercial data analysis software having tools which Subio Platform does not have. And you might think you cannot move to Subio Platform because you need the tools. If so, please consider our software development service. Although we charge on the development, it can be reasonable if your take into account license fees of following years.
|Working with R/Bioconductor for further statistical analysis.||Detail|
If you compare analysis software, you may focus on statistical features. But they are not everything to make your work easy and efficient. Please consider the following points.
|Items||Subio Platform||GeneSpring or
other commercial software
|R + Bioconductor||Excel + PDF|
|Visual aid with interactive operations|
|Statistical analysis tools, automation|
|To allow trials and errors,
or exploratory data mining
|Data sharing, co-working|
|Cost of using by team|
|Technical support, training|
|Extensibility (functions, data size,
number of participants)
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We're happy to show you a demonstration of Subio Platform and Plug-ins via web meeting. Many are impressed by realizing the importance of watching data from multiple angles, which is usually ignored in text books or guides of statistical workflow. If you're in Europe or Africa, we can talk in the morning. If you're in America, we can talk in the evening. Please send a request with convenient time and date for you.
University College Cork, Lab Researcher
It is an excellent user interface and the tutorials are brilliant.
Univ. of Copenhagen, Professor/Manager
This subio software platform is very easy to handle, even you include several hundred patients. The response is extremely fast compare with other similar softwares. Al...
Very flexible and powerful solution. Great technical support. VERY good advisory support!