scAI-class: The scAI Class

In sqjin/scAI: integrative analysis of single-cell transcriptomic and epigenomic profiles

Description

The scAI object is created from a paired single-cell transcriptomic and epigenomic data. It takes a list of two digital data matrices as input. Genes/loci should be in rows and cells in columns. rownames and colnames should be included. The class provides functions for data preprocessing, integrative analysis, and visualization.

Details

The key slots used in the scAI object are described below.

Slots

raw.data

List of raw data matrices, one per dataset (Genes/loci should be in rows and cells in columns)

norm.data

List of normalized matrices (genes/loci by cells)

agg.data

Aggregated epigenomic data within similar cells

scale.data

List of scaled matrices

pData

data frame storing the information associated with each cell

var.features

List of informative features to be used, one giving informative genes and the other giving informative loci

fit

List of inferred low-rank matrices, including W1, W2, H, Z, R

fit.variedK

List of inferred low-rank matrices when varying the rank K

embed

List of the reduced 2D coordinates, one per method, e.g., t-SNE/FIt-SNE/umap

identity

a factor defining the cell identity

cluster

List of consensus clustering results

options

List of parameters used throughout analysis

sqjin/scAI documentation built on Nov. 19, 2020, 4:04 p.m.