RunTFIDF | R Documentation |
Run term frequency inverse document frequency (TF-IDF) normalization on a matrix.
RunTFIDF(object, ...)
## Default S3 method:
RunTFIDF(
object,
assay = NULL,
method = 1,
scale.factor = 10000,
idf = NULL,
verbose = TRUE,
...
)
## S3 method for class 'Assay'
RunTFIDF(
object,
assay = NULL,
method = 1,
scale.factor = 10000,
idf = NULL,
verbose = TRUE,
...
)
## S3 method for class 'StdAssay'
RunTFIDF(
object,
assay = NULL,
method = 1,
scale.factor = 10000,
idf = NULL,
verbose = TRUE,
...
)
## S3 method for class 'Seurat'
RunTFIDF(
object,
assay = NULL,
method = 1,
scale.factor = 10000,
idf = NULL,
verbose = TRUE,
...
)
object |
A Seurat object |
... |
Arguments passed to other methods |
assay |
Name of assay to use |
method |
Which TF-IDF implementation to use. Choice of:
|
scale.factor |
Which scale factor to use. Default is 10000. |
idf |
A precomputed IDF vector to use. If NULL, compute based on the input data matrix. |
verbose |
Print progress |
Four different TF-IDF methods are implemented. We recommend using method 1 (the default).
Returns a Seurat
object
https://en.wikipedia.org/wiki/Latent_semantic_analysis#Latent_semantic_indexing
mat <- matrix(data = rbinom(n = 25, size = 5, prob = 0.2), nrow = 5)
RunTFIDF(object = mat)
RunTFIDF(atac_small[['peaks']])
RunTFIDF(atac_small[['peaks']])
RunTFIDF(object = atac_small)
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