|FLOCK (FLOw Clustering without K) is a computational approach to flow cytometry analysis which:
1. Computationally determines the number of unique populations in high dimensional flow data using a rapid binning approach
2. Can handle non-spherical hyper-shapes
3. Maps populations across independent samples
4. Calculates many useful summary statistics
5. Finds the most informative parameters
6. Reduces subjective factors in manual gating
FLOCK requires a text file, generated from a FCS file, as input.
In order to define the populations in a given dataset collection for a given set of markers, run FLOCK on a super-set of FCS file. Use the Downsample and merge tool to concatenate and/or downsample datasets, and remove, edit or rearrange markers before running FLOCK on your favorite set of markers.
FLOCK attributes each event to a population and generates a text file.
The centroid file is a table containing the mean, median or geometric mean fluorescent intensity values of each marker within each population defined by FLOCK, as determined by the user.
The population score output is a table containing marker scores for each population. The score value is a number indicating the degree to which this population expresses each marker, as follows:
- 1 implies negative expression
- 2 implies low expression
- 3 implies positive expression
- 4 implies highly positive expression
hg clone https://toolshed.g2.bx.psu.edu/repos/immport-devteam/run_flock
|Minimum Galaxy Version
|using a FCS file that was converted/transformed to a text file