Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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

Oncogenic KRAS-driven type I interferon signalling primes pancreatic cancer for necroptosis.

Nature communications·2026
Same author

Maternal Krüppel-like factor 2 (KLF2)+ CD4 T cells promote fertility and fetal tolerance.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Memory T cell rapid recall is driven by memory-specific AP-1 recruitment determined by epigenome and co-factor interactions.

bioRxiv : the preprint server for biology·2026
Same author

Gene regulatory network determinants of rapid recall in human memory CD4+ T cells.

bioRxiv : the preprint server for biology·2025
Same author

Epigenetic and transcriptional programming of murine eosinophils in the esophagus.

Nature communications·2025
Same author

Silencing <i>TET1</i> expression alters the epigenomic landscape and amplifies transcriptomic responses to allergen in airway epithelial cells.

Environmental epigenetics·2025

Related Experiment Video

Updated: Jul 1, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.7K

Accelerating Single-Cell Sequencing Data Analysis with SciDAP: A User-Friendly Approach.

Michael Kotliar1, Andrey Kartashov2, Artem Barski1,3,4,2

  • 1Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.

Biorxiv : the Preprint Server for Biology
|March 11, 2024
PubMed
Summary
This summary is machine-generated.

The Scientific Data Analysis Platform (SciDAP) simplifies complex single-cell sequencing data analysis for biologists. It provides reproducible workflows for single-cell RNA, ATAC, and Multiome sequencing, eliminating the need for coding expertise.

Keywords:
CWLSciDAPSingle-cellscATAC-SeqscMultiomescRNA-Seq

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.6K

Related Experiment Videos

Last Updated: Jul 1, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.7K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.5K
An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.6K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell (sc) sequencing technologies, including scRNA, scATAC, and scMultiome, are crucial for understanding biological and disease mechanisms.
  • Manual analysis of sc data is challenging due to large data volumes, complex parameters, and difficulties in reproducing computational environments, impacting result reproducibility.
  • Existing analysis methods often require significant computational expertise and coding skills, creating a barrier for many biologists.

Purpose of the Study:

  • To present a user-friendly protocol for analyzing scMultiome sequencing data using the Scientific Data Analysis Platform (SciDAP).
  • To demonstrate how SciDAP enables biologists without computational expertise to perform complex sequencing data analysis.
  • To highlight the platform's capability to provide portable and reproducible analysis pipelines using Common Workflow Language (CWL).

Main Methods:

  • Utilized the Scientific Data Analysis Platform (SciDAP) for processing scMultiome sequencing data.
  • Employed pre-built computational pipelines within SciDAP designed for common scRNA-Seq, scATAC-Seq, and scMultiome analysis needs.
  • Executed analysis workflows using Common Workflow Language (CWL) for portability and reproducibility.

Main Results:

  • SciDAP successfully facilitated the analysis of scMultiome data, offering a user-friendly alternative to manual processing.
  • The platform's CWL-based pipelines ensure reproducibility and eliminate the need for coding expertise among biologists.
  • The described protocol is adaptable for analyzing other single-cell sequencing datasets, including scRNA-Seq, scATAC-Seq, and scVDJ-Seq.

Conclusions:

  • The Scientific Data Analysis Platform (SciDAP) democratizes single-cell sequencing data analysis by providing accessible, reproducible, and user-friendly computational tools.
  • SciDAP empowers biologists to leverage advanced sequencing technologies without requiring specialized bioinformatics or programming skills.
  • The platform enhances the reproducibility of scientific findings derived from single-cell multiomics data.