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Related Experiment Video

Updated: Mar 1, 2026

Pooled CRISPR-Based Genetic Screens in Mammalian Cells
09:05

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CRISPRcloud: a secure cloud-based pipeline for CRISPR pooled screen deconvolution.

Hyun-Hwan Jeong1,2, Seon Young Kim1,2, Maxime W C Rousseaux1,2

  • 1Department of Molecular and Human Genetics, Baylor College of Medicine, Howard Hughes Medical Institute, Houston, TX, USA.

Bioinformatics (Oxford, England)
|May 26, 2017
PubMed
Summary
This summary is machine-generated.

We developed CRISPRcloud, a cloud-based pipeline for analyzing pooled screening data. This tool simplifies the extraction, clustering, and analysis of next-generation sequencing files from pooled CRISPR screening experiments.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Pooled screening experiments generate large volumes of next-generation sequencing (NGS) data.
  • Analyzing this data requires specialized bioinformatics tools and infrastructure.
  • Existing methods can be complex and time-consuming for researchers.

Purpose of the Study:

  • To develop a user-friendly, cloud-based data analysis pipeline for pooled screening data.
  • To provide a secure web-based platform for extracting, clustering, and analyzing NGS files.
  • To facilitate the reanalysis of pooled CRISPR screening datasets.

Main Methods:

  • Development of a cloud-based platform named CRISPRcloud.
  • Implementation of algorithms for data extraction, clustering, and analysis of NGS files.
  • Creation of a secure, web-based interface for data visualization and interaction.

Main Results:

  • CRISPRcloud offers a streamlined workflow for deconvolution of pooled screening data.
  • The platform provides a user-friendly interface for analyzing complex NGS datasets.
  • Enables efficient reanalysis of existing pooled CRISPR screening datasets.

Conclusions:

  • CRISPRcloud is a valuable tool for researchers working with pooled screening data.
  • The platform simplifies complex bioinformatics analyses, accelerating research.
  • This framework is expected to promote the development of similar web-based bioinformatics tools for NGS data handling.