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Cell Diversity

Cell Diversity

The concept of a cell started with microscopic observations of dead cork tissue by Robert Hooke in 1665. Hooke coined the term "cell" based on the resemblance of the small subdivisions in the cork to the rooms that monks inhabited, called cells. About ten years later, Antonie van Leeuwenhoek became the first person to observe the living and moving cells under a microscope. In the century that followed, the theory that cells represented the basic unit of life developed.
Multicellular...

Cell Lines

Cell Lines

A cell line is a population of cells grown in vitro that can be subcultured over several generations. Normal cells cease to divide after a certain number of cell divisions, a process known as replicative senescence. This number, called the Hayflick limit, was conceptualized by Leonard Hayflick in 1961 when he observed that fetal cells grown in culture could only divide 40-60 times. This limit is due to the shortening of the telomeres during each round of cell division, preventing cell division...

Overview Of Cell Separation And Isolation

Overview Of Cell Separation And Isolation

Cell separation was first achieved in 1964 by S. H. Seal, who separated large tumor cells from the smaller blood cells using filtration. Two years later, Pohl and Hawk performed experiments on how cells respond differently to a nonuniform electric field based on the cell type. Such observations were the inception of cell separation methods, which allow isolating a single cell type from a heterogeneous sample.

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Related Experiment Video

Updated: Dec 6, 2025

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Published on: January 19, 2017

Jointly defining cell types from multiple single-cell datasets using LIGER.

Jialin Liu¹, Chao Gao¹, Joshua Sodicoff¹

¹Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Nature Protocols

|October 13, 2020

Summary

This summary is machine-generated.

This protocol details LIGER, an R package for integrating diverse single-cell sequencing datasets. It enables unbiased cell type definition by combining gene expression and epigenomic data for robust biological discovery.

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Last Updated: Dec 6, 2025

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

Area of Science:

Genomics
Computational Biology
Bioinformatics

Background:

High-throughput single-cell sequencing technologies offer powerful tools for cell type identification.
Integrating multi-modal and multi-context single-cell data remains a significant challenge for comprehensive cellular identity definition.

Purpose of the Study:

To provide a comprehensive, step-by-step protocol for utilizing the LIGER R package.
To demonstrate the joint definition of cell types from multiple single-cell datasets using LIGER.

Main Methods:

The protocol outlines data preprocessing, normalization, and joint factorization using integrative nonnegative matrix factorization.
It details quantile normalization, joint clustering, and visualization for integrated analysis.
The method is applicable to various data types, including single-cell RNA-seq (scRNA-seq) and single-nucleus ATAC-seq (snATAC-seq).

Main Results:

The LIGER protocol facilitates the integration of diverse single-cell datasets for unbiased cell type definition.
The open-source R implementation provides tutorials and examples for practical application.
Analysis can be completed rapidly (1-4 hours) without specialized bioinformatics expertise.

Conclusions:

LIGER offers a robust and accessible framework for integrating multi-modal single-cell data.
This protocol empowers researchers to define cellular identities more accurately across different biological contexts and data types.
The approach supports a wide range of applications, including cross-species and spatial analyses.