View source: R/clustering_WADB_wrapper.R
clusteringWADB_Wrapper | R Documentation |
This function executes the whole autoencoder pipeline
clusteringWADB_Wrapper(
group = c("sudo", "docker"),
scratch.folder,
file,
separator,
nCluster,
permutation,
nEpochs,
patiencePercentage = 5,
seed = 1111,
projectName,
lr = 0.01,
loss = "mean_squared_error",
clusterMethod = c("GRIPH", "SIMLR", "SEURAT", "SHARP"),
pcaDimensions = 5,
Sp = 0.8
)
group |
a character string. Two options: sudo or docker, depending to which group the user belongs |
scratch.folder |
a character string indicating the path of the scratch folder |
file |
a character string indicating the path of the file, with file name and extension included |
separator |
separator used in count file, e.g. '\t', ',' |
nCluster |
number of cluster in which the dataset is divided |
permutation |
number of permutations to perform the pValue to evaluate clustering |
nEpochs |
number of Epochs for neural network training |
patiencePercentage |
number of Epochs percentage of not training before to stop. |
seed |
important value to reproduce the same results with same input |
projectName |
might be different from the matrixname in order to perform different analysis on the same dataset |
lr |
learning rate, the speed of learning. Higher value may increase the speed of convergence but may also be not very precise |
loss |
loss of function to use, for other loss of function check the keras loss of functions. |
clusterMethod |
clustering methods: "GRIPH","SIMLR","SEURAT","SHARP" |
pcaDimensions |
number of dimensions to use for Seurat Pca reduction. |
Sp |
minimun number of percentage of cells that has to be in common between two permutation to be the same cluster. |
folders the complete autoencoder analysis.
Luca Alessandri, alessandri [dot] luca1991 [at] gmail [dot] com, University of Torino
## Not run:
clusteringWADB_Wrapper(group=c("sudo"),scratch.folder="/home/user/scratch",file="/home/user/autoencoderClustering_v4/u/setA.csv",separator=",",nCluster=5,permutation=80,nEpochs=1000,patiencePercentage=5,seed=1111,projectName="yuppy",clusterMethod=c( "SIMLR"),lr=0.001)
## End(Not run)
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