runTSNE: Run tSNE from (R pkg 'Rtsne') on a GatingSet
In seshadrilab/flowHelpers: Collection of helper functions for analyzing FCM data

Description Usage Arguments Details Value

- If groupBy is empty, no sampling is done. If length is 1, equal number of cells are sampled from each category in the column. If length is 2, equal number of cells are sampled from each category in the first column. Additionally, within each category, equal numbers of cells are sampled from the second column (usually the Sample names column).

runTSNE(gs = NULL, parentGate = NULL, degreeFilterGates = c(),
  otherGates = c(), tsneMarkers = c(), groupBy = c(),
  degreeFilter = 0, seed = 999, theta = 0.9, numThreads = 1,
  cloneGs = TRUE, n = NULL, ...)

`gs`	a GatingSet object or path to a GatingSet directory, properly gated data with annotation in its pData
`parentGate`	a `string` describing the gate upstream of the cytokine gates (eg. "CD4", "cd8+", etc...)
`degreeFilterGates`	a `vector` of `strings` describing the marker gates immediately downstream of parentGate, eg: "CD4/IL2", "CD4/IFNg". Events are assigned degrees based on how many degreeFilterGates they belong to
`otherGates`	a `vector` of `strings` describing additional gates to obtain boolean data for (gate membership is assigned to each cell)
`tsneMarkers`	the markers on which to run tSNE. Although data from all markers will be returned, tSNE is only run on the markers specified in tsneMarkers
`groupBy`	a `vector` of `strings` describing columns of the `gatingSet`'s phenoData. Affects sampling (see function description).
`degreeFilter`	keep cells of this degree and higher
`seed`	since tSNE is random, need a random seed so we can reproduce results
`theta`	parameter to be passed to the `Rtsne` function
`numThreads`	if > 1, uses multicore t-SNE instead of regular t-SNE
`cloneGs`	boolean for whether to to clone the GatingSet. Cloning is safer when gs is a GatingSet object because the GatingSet may get modified in this function. Cloning takes up time and memory, however, so if you are not using the in-memory-GatingSet again you can choose FALSE.
`...`	other parameters to be passed to the `Rtsne` function

- All channels must have non-NA marker names and be unique.

- Requires a valid GatingSet with cytokine gates downstream of a parent gate - Also expects that pData(gs) contains at least columns: 'name', 'ptid' so we can identify cells later

TODO: allow option to use pre-sampled GatingSet (to save time) and/or save sampled GatingSet to disk...

a matrix of X and Y coordinates

seshadrilab/flowHelpers documentation built on May 23, 2019, 4:05 a.m.