How do I export the attributes for a file?Īs of SPADE 1.6 (or bioconductor version 1.10), the attribute tables are automatically produced in output/tables. If this is a problem for you, contact the developers for help Newer versions of the "Generate PDFs" script are not backward compatible with results generated by 0.2* era SPADE. If you are upgrading from the 0.2+ versions, we don't think there should be any incompatibilities, except for "Generate PDFs" for those upgrading from version 0.2*. Note: If you are upgrading from a very old version of SPADE, i.e., from November 2010, talk to the developers beforehand as the newer versions are not backward compatible with results from the oldest SPADE versions. Follow the instructions on the ] page for installing the R-package and Cytoscape plugin. You need to re-install both the R-package and the Cytoscape plugin as the two are developed "in-sync" with each other, and differing versions might not be compatible. Then, when setting up the clustering step in SPADE, select only the parameters without the brackets. Alternately you can exported compensated data without the compensation matrix, or export uncompensated data with the compensation matrix. So what should I do? The easiest approach is make sure you export both compensated and uncompensated data, along with the compensation matrix. The error you might see in the former case is something like: Error: The following parameters in the spillover matrix In this case, SPADE finds the compensation matrix and attempts to apply the compensation only to not find the parameters (because FlowJo inserted brackets in the name) or it "double" compensates.
However, problems emerge if you export only compensated data (often indicated by angle brackets in FlowJo generated files) AND also export the compensation matrix. SPADE by default compensates FCS data if it finds the compensation matrix in the SPILL or SPILLOVER keyword in the FCS file. If you have a success story, or run into problems using SPADE for a secondary indication, please let us know! File an issue or story here. Gene expression data might behave similarly but will depend on the distribution of signals for each channel. Fluorescence cytometry datasets where around six clustering channels are used might target 50 to 100 nodes. The defaults intended for mass cytometry data are 200 nodes and 10% of cells, assuming 10 to 15 clustering channels and >100,000 cells. (This depends on how heterogeneous your sample is.) The following setting would target 90% of your cells: downsampling_target_percent=0.9Īs when analyzing flow cytometry data, you should increase the target number of nodes slightly for each clustering parameter added. 1000), it might be desirable to disable downsampling, or not downsample much. Whether you want to do that or not ahead of time is up to you and how you think your data will look.īecause most gene expression data sources yield information for a relatively small number of cells (e.g. If it's not already transformed, you could have SPADE do the log transform for you: TRANSFORMS=flowCore::logTransform(logbase=2) # for base 2 If your data is already transformed, then you should set a linear transform with an argument of 1 when running SPADE: TRANSFORMS=flowCore::linearTransform(a=1)
In cytometry, this is usually an ArcSinh-like transformation in gene expression, this is usually a log transformation. Often, it is desirable to transform your data.
#Flowjo 10 downsample software#
The best first step is to convert your data to an FCS file using software such as Mathematica, Matlab or R and then just try running SPADE. However, theoretically it will work with any sort of tabular data (e.g. SPADE was designed to work with flow (fluorescence) and mass cytometry (CyTOF) data. How do I use SPADE on non-cytometry data?
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