run_scINSIGHT {scINSIGHT}

Perform scINSIGHT on normalized datasets

Description

Perform INterpreting single cell gene expresSIon bioloGically Heterogeneous daTa (scINSIGHT) to return factorized W_{\ell1}, W_{\ell2}, H and V matrices.

This factorization produces a W_{\ell1} matrix (cells by K_j), a W_{\ell2} matrix (cells by K), a shared V matrix (K by genes) for each sample, and a H (K_j by genes) matrix for each condition. W_{\ell2} are the expression matrices of K common gene modules for all samples, V is the membership matrix of K common gene modules, and it's shared by all samples. W_{\ell1} are the expression matrices of K_j condition-specific gene modules for all samples, and H are the membership matrices of K_j condition-specific gene modules for all conditions.

Usage

run_scINSIGHT(
  object,
  K = seq(5, 15, 2),
  K_j = 2,
  LDA = c(0.001, 0.01, 0.1, 1, 10),
  thre.niter = 500,
  thre.delta = 0.01,
  num.cores = 1,
  B = 5,
  out.dir = NULL,
  method = "increase"
)

Arguments

object

scINSIGHT object.

K

Number of common gene modules. (default c(5, 7, 9, 11, 13, 15))

K_j

Number of dataset-specific gene modules. (default 2)

LDA

Regularization parameters. (default c(0.001, 0.01, 0.1, 1, 10))

thre.niter

Maximum number of block coordinate descent iterations to perform. (default 500)

thre.delta

Stop iteration when the reduction of objective function is less than the threshold. (default 0.01)

num.cores

Number of cores used for optimizing factorizations in parallel (default 1).

B

Number of repeats with random seed from 1 to B. (default 5)

out.dir

Output directory of scINSIGHT results. (default NULL)

method

Method of updating the factorization (default "increase"). If provide multiple K, user can choose method between "increase" and "decrease".

For "increase", the algorithm will first perform factorization with the least K=K_1. Then initialize K_2-K_1 facotrs, where K_2 is the K sightly larger than K_1, and perform facotrization with these new facotrs. Continue this process until the largest K.

For "increase", the algorithm will first perform factorization with the largest K=K_1. Then choose K_2 facotrs, where K_2 is the K sightly less than K_1, and perform facotrization with these new facotrs. Continue this process until the least K.

Value

scINSIGHT object with W_1, W_2, H, V and parameters slots set.