impute | R Documentation |

Performs imputation of dropout values in scRNA-seq data using ccImpute algorithm

impute( logX, useRanks = TRUE, pcaMin, pcaMax, k, consMin = 0.65, nCores, kmNStart, kmMax = 1000 )

`logX` |
A normalized and log transformed scRNA-seq expression matrix. |

`useRanks` |
A Boolean specifying if non-parametric version of weighted Pearson correlation should be used. |

`pcaMin` |
This is used to establish the number of minimum PCA features
used for generating subsets. For small datasets up to |

`pcaMax` |
This is used to establish the number of maximum PCA features
used for generating subsets. For small datasets up to |

`k` |
centers parameter passed to |

`consMin` |
the low-pass filter threshold for processing consensus matrix. |

`nCores` |
the number of cores to be used on the user's machine.
If not set, |

`kmNStart` |
nstart parameter passed to |

`kmMax` |
iter.max parameter passed to |

A normalized and log transformed scRNA-seq expression matrix with imputed missing values.

exp_matrix <- log(abs(matrix(rnorm(1000000),nrow=10000))+1) impute(exp_matrix, k = 2, nCores = 2)

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