Description Usage Arguments Value Examples
This function takes a data matrix as input and out puts the parameters asscociated to the MP distribution.
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expr |
a data matrix with cells in the columns and genes in the rows, preferably standardized gene-wise |
sample |
TRUE/FALSE, if the parameters should be estimated by random sampling or not, default is FALSE |
cor |
TRUE/FALSE, if the svd should be calculated on the correlation matrix or not (covariance matrix), default is TRUE |
nu |
the number of gene singular vectors to calculate in the process (the more, the more time expansive), default is 50 |
p.val |
the p-value to be used in the test of normality for the singular vectors, default is 0.01 |
A MP object:
eigen: eigenvalues and vectors of the cell-cell correlation matrix
maxEigen: maximum eigenvalue of the MP distribution
minEigen: minimum eigenvalue of the MP distribution
sig_vectors: singular vectors that lie significantly above the MP distribution
M: the number of genes
N: the number of cells
svd: the singular value decomposition
genes.used: genes that have been used for the calculation of the MP distribution
p.value_mp_fit: p-value for the similarity of a MP distribution to the eigenvalues found as noise
transcriptome_mode: the index of the transcriptome mode
input_parameters: the inputs to the function
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