Title: | Single-Cell Integrator and Batch Effect Remover |
---|---|
Description: | Remove batch effects by projecting query batches into the reference batch space. |
Authors: | Dailin Gan [aut, cre] |
Maintainer: | Dailin Gan <[email protected]> |
License: | MIT + file LICENSE |
Version: | 0.2.1 |
Built: | 2025-02-20 03:44:45 UTC |
Source: | https://github.com/ravengan/sciber |
A dataset human dendritic cells gene expression and corresponding meta data
HumanDC
HumanDC
An object of class list
of length 2.
https://pubmed.ncbi.nlm.nih.gov/28428369/
Batch effect removal with SCIBER
SCIBER( input_batches, ref_index = NULL, batches_meta_data = NULL, omega = 0.5, h_fisher = 75, n_core = parallel::detectCores(), seed = 7, k = NULL )
SCIBER( input_batches, ref_index = NULL, batches_meta_data = NULL, omega = 0.5, h_fisher = 75, n_core = parallel::detectCores(), seed = 7, k = NULL )
input_batches |
A list contains all the pre-processed matrices with dimension of n_genes*n_cells. |
ref_index |
The index of the reference batch in the object "input_batches" |
batches_meta_data |
A list contains the meta data for all the batches. The order should be consistent with that in "input_batches". Each meta data contains three columns, "cell_id", "cell_type", and "dataset". "dataset" indicates which batch the data comes from. The row names of meta data should match the column names of batch. |
omega |
A list of proportion of matched clusters or a single value between 0 and 1 applied to all query batches. |
h_fisher |
The number of marker genes used for Fisher exact test. |
n_core |
Specify the number of cores otherwise use all the available cores. |
seed |
random seed. |
k |
Number of clusters used for K-means. If not provided, the default is k = the square root of n_0, where n_0 is the number of cells in the reference batch. |
A list which contains the reference and batch-effect-corrected batches. The order is the same as that in input_batches.
data(HumanDC) exp <- HumanDC[["exp"]] meta <- HumanDC[["metadata"]] omega <- c() omega[[1]] <- 0.5 res <- SCIBER(input_batches = exp, ref_index = 1, batches_meta_data = meta, omega = omega, n_core = 1)
data(HumanDC) exp <- HumanDC[["exp"]] meta <- HumanDC[["metadata"]] omega <- c() omega[[1]] <- 0.5 res <- SCIBER(input_batches = exp, ref_index = 1, batches_meta_data = meta, omega = omega, n_core = 1)