runTrex | R Documentation |
Run Trex algorithm with Seurat or SingleCellExperiment pipelines
runTrex(
sc,
chains = "TRA",
method = "encoder",
encoder.model = "VAE",
encoder.input = "AF",
theta = pi,
reduction.name = "Trex"
)
sc |
Single Cell Object in Seurat or SingleCell Experiment format |
chains |
TRA or TRB |
method |
"encoder" = using deep learning autoencoders or "geometric" = geomteric transformations based on BLOSUM62 matrix |
encoder.model |
"AE" = dense autoencoder or "VAE" = variation autoencoder |
encoder.input |
Atchley factors (AF), Kidera factors ((AF)), or or One-Hot Encoder (OHE). |
theta |
angle to use for geometric transformation |
reduction.name |
Keyword to save Trex reduction. Useful if you want to try Trex with multiple parameters |
Seurat or SingleCellExperiment object with Trex dimensions placed into the dimensional reduction slot.
trex_example <- runTrex(trex_example,
chains = "TRA",
method = "encoder",
encoder.model = "VAE",
encoder.input = "AF")
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