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

You might also read

Related Articles

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

Sort by

Same author

Saturation Genome Editing reveals the functional impact of RAD51D <i>and</i> XRCC2 variants.

bioRxiv : the preprint server for biology·2026

Same author

Embryo-scale Visual Cell Sorting reveals a conserved transcriptomic signature of nucleolar size linked to proteostasis.

bioRxiv : the preprint server for biology·2026

Same author

Evidence for G6PD variant classification from multiplexed functional assays.

Genome biology·2026

Same author

Phenotype-Specific Recalibration of MAVE Data Enables Repurposing of <i>BAP1</i> Functional Assays for Küry-Isidor Syndrome.

medRxiv : the preprint server for health sciences·2026

Same author

Not Forgotten: Patient Experiences with Genetic Variant Reclassifications.

medRxiv : the preprint server for health sciences·2026

Same author

Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects.

Cell·2026

Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026

Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026

Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026

Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026

Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026

Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 8, 2026

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

CountESS: a flexible, graphical pipeline tool for deep mutational scanning analysis.

Nick Moore¹, Callum J Sargeant¹, Matthew J Wakefield^1,2

¹The University of Melbourne, Melbourne, Victoria, Australia.

Biorxiv : the Preprint Server for Biology

|May 7, 2026

Summary

This summary is machine-generated.

CountESS is a new open-source tool that simplifies complex Deep Mutational Scanning (DMS) data analysis. It offers a flexible, graphical interface to process diverse experimental designs and generate variant scores efficiently.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Related Experiment Videos

Last Updated: May 8, 2026

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Deep Mutational Scanning (DMS) experiments generate extensive sequencing data requiring multi-step computational analysis.
Existing DMS analysis tools are fragmented, lacking flexibility for diverse experimental designs and scoring strategies.

Purpose of the Study:

To introduce CountESS, an open-source pipeline tool for flexible and efficient Deep Mutational Scanning (DMS) data analysis.
To provide a modular, graphical interface that accommodates a wide range of DMS experimental workflows.

Main Methods:

Developed CountESS, an open-source pipeline tool using Python and DuckDB.
Implemented a modular graphical interface supporting various input formats, barcode translation, HGVS variant calling, and user-defined scoring functions.
Ensured high-performance, memory-efficient processing for large datasets.

Main Results:

CountESS accommodates diverse DMS experimental designs, including selection assays, time-series, and bin-based assays like VAMP-seq.
The tool supports user-defined scoring functions, enhancing analytical flexibility.
Demonstrated high-performance and memory efficiency for processing large sequencing datasets.

Conclusions:

CountESS provides a unified, flexible, and efficient solution for Deep Mutational Scanning (DMS) data analysis.
The open-source nature and modular design of CountESS promote broader adoption and customization in biological research.