View source: R/markerGenesAndMapping.r
possibleClustersByPriors | R Documentation |
This function will return a vector of possible clusters for cells that meet a set of priors for each layer
possibleClustersByPriors(
cluster,
layer,
subsetVector = rep(TRUE, length(cluster)),
useClusters = sort(unique(cluster)),
rareLimit = 0.005,
layerNm = c("L1", "L2/3", "L4", "L5", "L6"),
scaleByLayer = TRUE,
scaleByFn = max,
smartWeight = TRUE,
spillFactor = 0.15,
weightCutoff = 0.02
)
cluster |
vector of all clusters |
layer |
list of layers for each cluster entry (for data sets with only laminar dissections, each list entry will be of length 1) |
subsetVector |
a vector of TRUE/FALSE values indicated whether the entry is in the subset of interest (e.g., Cre lines); default is all |
useClusters |
a set of clusters to be considered a priori (e.g., GABA vs. glut); default is all |
rareLimit |
define any values less than this as 0. The idea is to exclude rare cells |
layerNm |
names of all layers. set to NULL to have this calculated |
scaleByLayer |
if TRUE, scales to the proportion of cells in each layer |
scaleByFn |
what function should be used for the layer scaling (default=max, ignored if scaleByLayer=FALSE) |
smartWeight |
if TRUE, multilayer dissections are weighted smartly by cluster, rather than evenly by cluster (FALSE) |
spillFactor |
fractional amount of cells in a layer below which it is assumed no cells are from that layer in multilayer dissection |
weightCutoff |
anything less than this is set to 0 for convenience |
a vector of possible clusters for cells that meet a set of priors for each layer
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.