Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

From Fundamental Photophysics to Photocatalysis: Energy Gap Law Analysis of Anion Radical Excited States.

ACS central science·2026

Same author

Tumor-naïve ctDNA detection with deep learning-enhanced error suppression for sensitive mutation calling.

Genome medicine·2026

Same author

VariantMedium: sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental data.

Genome medicine·2026

Same author

Cell shapes decode molecular phenotypes in image-based spatial proteomics.

Cell systems·2026

Same author

Analysis of ovarian cancer immune cell profile identifies immunosuppressive states associated with adverse clinical attributes and survival times.

PloS one·2026

Same author

Five-year cardiovascular outcomes following COVID-19-associated carditis.

Clinical research in cardiology : official journal of the German Cardiac Society·2026

Same journal

AlliGator: Open source fluorescence lifetime imaging analysis in G.

SoftwareX·2026

Same journal

ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis.

SoftwareX·2026

Same journal

scSpatialSIM: a simulator of spatial single-cell molecular data.

SoftwareX·2026

Same journal

HistomicsTK: A Python toolkit for pathology image analysis algorithms.

SoftwareX·2025

Same journal

SWCRTsimulator: A simulation-based platform for power estimation in stepped wedge cluster randomized trials with interval-censored outcomes.

SoftwareX·2025

Same journal

ContDataQC: An R package and Shiny app for quality control of continuous water quality sensor data.

SoftwareX·2025

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 6, 2025

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

TumorDecon: A digital cytometry software.

Rachel A Aronow¹, Shaya Akbarinejad¹, Trang Le¹

¹Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, 01003, USA.

|July 5, 2022

Summary

This summary is machine-generated.

TumorDecon is a new Python package that simplifies the analysis of tumor immune cell composition from RNA sequencing data. It offers accessible digital cytometry methods to efficiently characterize immune profiles.

Keywords:

CIBERSORT DeconRNASeq Deconvolution methods Digital cytometry Signature matrix SingScore ssGSEA

More Related Videos

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Published on: June 8, 2019

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Published on: February 28, 2014

Related Experiment Videos

Last Updated: Sep 6, 2025

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

Published on: September 4, 2017

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Published on: June 8, 2019

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Adaptation of Semiautomated Circulating Tumor Cell CTC Assays for Clinical and Preclinical Research Applications

Published on: February 28, 2014

Area of Science:

Computational biology
Immunology
Bioinformatics

Background:

Experimental immune profiling of tumors using methods like flow cytometry is resource-intensive.
Digital cytometry methods offer an alternative by estimating cell frequencies from RNA sequencing (RNA-seq) data.

Purpose of the Study:

To introduce TumorDecon, a Python package for deconvolving immune cell distribution from bulk tumor RNA-seq data.
To provide an accessible and efficient tool for tumor immune profiling.

Main Methods:

TumorDecon implements four distinct deconvolution algorithms.
The package includes curated gene sets and signature matrices for analysis.
It also supports the generation of custom signature matrices.

Main Results:

TumorDecon facilitates the application of digital cytometry methods.
It enables the characterization of immune cell composition within tumors using RNA-seq.

Conclusions:

TumorDecon offers a user-friendly and efficient approach to tumor immune profiling.
This tool can help overcome the limitations of traditional experimental methods for immune cell characterization.