I believe that what we face at present is a turning point. The flow data we are able to generate are getting too complex to be understood by the old ways of data analysis (gate, show, compare to other samples you remember). If you have a set of 100+ samples and 1mil cells in each tube ... What can you do? The way to go is to use the approaches use for example in microarray data analysis. However, there are no miracle softwares that would give you THE ANSWER. I think we (flow people) have to educate ourselves in the data analysis tools, we should learn how to use BioConductor / R-project tools. Or, we should have a mathematician/bioinformatician available in our team to help us. As a graphical front end to R-project you can use "Rstudio", but the bottom line is, you need to understand what are you doing. So the flow data analysis of the (near) future is a combination of pattern recognition (the good old way) AND a sophisticated computational approaches. So in my view the question you should ask is: What competence should a flow data analyst have? Where can I learn such things? And only secondary to that is what are the software tools you can use.
Check out the various Bioconductor packages using the R computing environment. Our group has contributed FlowFP but there are others. These all use newer algorithms based on such things as probability binning (thanks Mario) that are much more powerful that flowjo or Kaluza which are conventionally based.
I would recommend FlowJo. I think you can try it for free with 30-day trial.
There are few more softwares available including WinMDI, but FlowJo is much more advanced. You can load FCS files to it.
I routinely use FACSDiva which is installed on LSR II I use and I like this software overall. However, if I need to do some analysis at home, I use FlowJo.
FlowJo for Mac (v9.x) rules. Java version (so called PC version), including newly released FlowJo X sucks. I've tried Kaluza - it does not handle big files very well. And I've never met "hardcore-flowjo-users" who tried Kaluza and liked it.
The main analytical focus of the most widely used industry software, such as FlowJo and FCS Express, is manual gating. Such software with large user bases are understandably slow to change, and perhaps reluctant to provide users with analysis tools that are not widely recognized.
Currently available software providing automated analysis methods include the more generalized analysis packages such as the flow cytometry suite, and specialized tools such as that provided by the authors of the recently published automated analysis technique
The FC analysis libraries available through the Bioconductor project are excellent, yet, while being based on R has many benefits, it is at its core a command-line based software. For many users, command-line access is a foreign concept, and this fact alone will prevent them from ever trying it. However, far from being in competition with Bioconductor, there is potential for FIND to make use of Bioconductor through a bridge library, RPy, that allows access to R functionality from Python programs. The program Flow suffers from similar problems in the area of usability. The interface itself can be confusing and tends to be overly technical, as is the documentation which states the program is aimed more at developers than end-users. Software in the category of algorithm-specific programs, such as the webservice FLAME, certainly serve a useful purpose, but offer no generality or measures for comparison to other methods. No algorithm will be appropriate for every dataset, and continuity of interface is important for work-flow efficiency.
It is very difficult to work in a team, because the working spaces generated are absolutely dependent on the fcs' place in your directories in your computers. Latest versios still lack automatic clustering algorithms like the very useful "snap-into" gate of the late FACSDiva software.
Another option you might want to consider is Cytobank: http://www.cytobank.org/
There is free online-based version and a paid hosted version available. I think the strongest features of the software are the data annotation and collaborative file sharing.
I find FCS Express the best value for money - although not free it is much cheaper than alternatives (we first started using it when little was available for running on PC's since software for Macs dominated). You get a month's free trial so you can give it a try to decide whether you like it.
Hello All, Being part of the development team for Inivai - FlowLogic, my answer is biased, but I do like using FlowLogic. A complete analytical package, great for batch analysis, plate analysis, statistical significance testing and graphing. Well worth checking out, Inivai have a 30 day free trial on a complete working version. They have quick guides and videos to get you started ASAP. Here's the link if interested
Thank you all, but I was wrong doing my question: I don't need an analysis software. I currently know and use DIVA, FlowJO, CellQuest, WinMDI (at the beginning of my career, Lysis...does anyone remember it? :))
Today I am in the turn of considering which is the best way to understand and show multicolor data.
The only one software I know is SPICE.
"SPICE is a data mining software application that analyzes large FLOWJO data sets from polychromatic flow cytometry and organizes the normalized data graphically. SPICE enables users to discover potential correlations in their experimental data within complex data sets." (cited from SPICE homepage).
SPICE allows you to have three different kind of visualization of your results, histogram bars, +/-, and pies (sorry, I can't attach a figure, the attachment tool doesn't work). I think it is a good way to have a correct "feeling" of complex data such as those generated from multicolor staining, especially in intracellular staining, when you study the simultaneous production of several cytokines in your population of interest.
Now I can re-formulate my question: does anyone know other data mining software dedicated to interpretation/visualization of multicolor flow cytometry results as "SPICE" does?
You can try Weasel, up-to-date, full of features and relatively cheap (and with a generous trial period).
If you have programming skills, know somebody that knows about it or can hire somebody, a very good option is to use the R statistical environment (www.r-project.org) with flow cytometry related packages (http://www.bioconductor.org/packages/release/BiocViews.html#___FlowCytometry). There, the sky is the limit.
I forgot, bot options (Weasel and R) run in any software platform (Windows, Linux, MacOS, etc.). This is really important for me (I work with MacOS and Linux, some students with Linux, other with Windows, some colleagues with MacOS, other with Windows).
I believe that what we face at present is a turning point. The flow data we are able to generate are getting too complex to be understood by the old ways of data analysis (gate, show, compare to other samples you remember). If you have a set of 100+ samples and 1mil cells in each tube ... What can you do? The way to go is to use the approaches use for example in microarray data analysis. However, there are no miracle softwares that would give you THE ANSWER. I think we (flow people) have to educate ourselves in the data analysis tools, we should learn how to use BioConductor / R-project tools. Or, we should have a mathematician/bioinformatician available in our team to help us. As a graphical front end to R-project you can use "Rstudio", but the bottom line is, you need to understand what are you doing. So the flow data analysis of the (near) future is a combination of pattern recognition (the good old way) AND a sophisticated computational approaches. So in my view the question you should ask is: What competence should a flow data analyst have? Where can I learn such things? And only secondary to that is what are the software tools you can use.
@Tomas: you are right. But I am lucky, because I can be helped by a bioinformatician! Maybe putting togheter our skills we can reach some goal... Thank you.
@Thomas: I agree, these are exciting times for flow cytometry. Learning multivariate analysis and such should be one of the aims of a flow data analyst. I have started to analyze some of my data with R (directly from the FCS files), and the results are very encouraging.
As a user of R I recommend you use the packages from Bioconductor project. In fact, there is an excellent workflow on Flow Cytometry in the BioConductor web page:
Also, you may have a look at the Courses & Conferences section (http://www.bioconductor.org/help/course-materials/) , where you can found some meterials about this task (http://www.bioconductor.org/help/course-materials/2007/BioC2007/labs/flowcore1/)