Single cell RNA-seq data analysis, without coding

Turn your single cell RNA-sequencing data into meaningful insight with Trailmaker®

Explore supported data from 10x Genomics™ Chromium™, Parse Biosciences Evercode™ and BD Rhapsody™ — from quality control and sample integration to gene expression and publication-ready figures.

Free for all academic researchers (including those who are not Parse customers).

Analyze your data

Looking for the Biomage-hosted community instance of Cellenics®?

Following Biomage’s acquisition, the Biomage-hosted instance of Cellenics® is now Trailmaker®.
Trailmaker® offers all the capabilities of Cellenics®, allowing you to go from count matrices of any single cell technology provider to publication-ready figures without writing a single line of code.
All scientific data is preserved within your account.
Access remains FREE for all academic users.

Learn more

Free certified course: Mastering Single Cell RNA-seq Data Analysis

This comprehensive course is designed to equip you with the knowledge and skills needed to analyze single cell RNA-seq data using Trailmaker®. From data uploading and processing to integration, exploration, and visualization, we will cover everything you need to know to become an expert in single cell RNA-seq data analysis.

Included in the online course: 41 video lessons over 9+ hours that you can watch at your own pace + downloadable PDF course material.

Register here

Papers that cite the Biomage-hosted instance of Cellenics®

Want to read about the publications that have used the Biomage-hosted community instance of Cellenics® for their data analysis? Read a selection below!

“Polybacterial intracellular coinfection of epithelial stem cells in periodontitis” by Easter et al (2023)
https://www.biorxiv.org/content/10.1101/2023.08.23.554343v1.full
“Lymphoid tissues contribute to viral clonotypes present in plasma at early post-ATI in SIV-infected rhesus macaques” by Solis-Leal et al (2023)
https://www.biorxiv.org/content/10.1101/2023.05.30.542512v1.full
“MARCO in alveolar macrophages negatively regulates Ace expression and aldosterone production” by O’Brien et al (2023) elife
https://elifesciences.org/reviewed-preprints/91318
“Efferocytosis is restricted by axon guidance molecule EphA4 via ERK/Stat6/MERTK signaling following brain injury” by Soliman et al (2023) J Neuroinflammation
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10633953/
“ENPP1 is an innate immune checkpoint of the anticancer cGAMP-STING pathway” by Wang et al (2023)
https://www.biorxiv.org/content/10.1101/2023.06.01.543353v1.full

What members of the Biomage community of Cellenics® users are saying:

“Cellenics® has dramatically reduced the learning curve for exploring single cell RNA-seq datasets. As a student, it has allowed improved communication between my mentor and myself while processing, visualizing, and exploring our dataset. This saves a tremendous amount of time.”

Dr Sawyer Hicks, University at Albany
“Cellenics® is a brilliant tool for analysing single cell RNAseq data for novices. It takes the pain out of QC and pre-processing of raw count data, with an easy-to-use graphical user interface without the pain of having to learn R. Once the data is processed, Cellenics® allows data interrogation and visualization in many different ways. This makes it quick and easy to generate publication-quality graphics files in a variety of file formats for inclusion in grant applications or manuscripts.”

Assistant Prof Duncan Sparrow, University of Oxford
“Cellenics® is great - it will be a really useful analytical tool for the scRNA-seq community, both for novice users and for labs like mine that already do their own analysis with Seurat.”

Prof John Campbell, University of Virginia
“I attended yesterday’s seminar regardingthe Biomage-hosted instance of Cellenics® and was quite impressed about this tool. This seminar was actually delivered in a really good timing for me since I was about to start watching a lot of tutorials to learn how to use R and Seurat to analyze 10x Genomics data that we just received. So, you can imagine how happy I am to be able to skip all that and just go ahead and analyze my data!”

Antonio Solis, Texas Biomedical Research Institute
I would like to thank you and your team for the kind support and for building such a helpful tool. After using the Biomage-hosted community instance of Cellenics® for a few days, I was able to analyze the data without any prior knowledge of single-cell RNA sequencing data analysis.

Dinuka Adasooriya

Meet our team

At Biomage, we are deeply passionate about the goal of improving human health. We are achieving this goal by enabling scientific researchers to discover new drug targets and answer deep biological questions from transcriptomics data.

Our expert team of bioinformaticians, software engineers and scientists take away technical difficulties and bring clarity to 'big data' using accessible and intuitive tools.

Single cell RNA-seq data analysis, without coding

Turn your single cell RNA-sequencing data into meaningful insight with Trailmaker®

Looking for the Biomage-hosted community instance of Cellenics®?

Free certified course: Mastering Single Cell RNA-seq Data Analysis

Papers that cite the Biomage-hosted instance of Cellenics®

Want to read about the publications that have used the Biomage-hosted community instance of Cellenics® for their data analysis? Read a selection below!

“Cellenics® has dramatically reduced the learning curve for exploring single cell RNA-seq datasets. As a student, it has allowed improved communication between my mentor and myself while processing, visualizing, and exploring our dataset. This saves a tremendous amount of time.”

“Cellenics® is great - it will be a really useful analytical tool for the scRNA-seq community, both for novice users and for labs like mine that already do their own analysis with Seurat.”

I would like to thank you and your team for the kind support and for building such a helpful tool. After using the Biomage-hosted community instance of Cellenics® for a few days, I was able to analyze the data without any prior knowledge of single-cell RNA sequencing data analysis.

Meet our team

Learn more about our team members