1 - 5 of 5 results


A package based on a parameterization-free method for combining multitube FCM data into a higher-dimensional form suitable for deep profiling and discovery. FlowBin allocates cells to bins defined by the common markers across tubes in a multitube experiment, then computes aggregate expression for each bin within each tube, to create a matrix of expression of all markers assayed in each tube. It is designed to accept multiple FCM assays from the same multitube assay and combine these into a complete matrix of measurements for all the markers. To this end, flowBin consists of four stages: (i) normalization, (ii) binning, (iii) bin matching across tubes and (iv) expression measurement. Compared with NNs merging of tubes, flowBin produces cleaner data, with far fewer false double-positive marker combinations.


Removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test.