Adam Cribbs

work led by
Jianfeng sun,
with fantastic collaborators Shuang Li, Stefan Canzar

UMIche features:
🧠 mclUMI (Markov clustering)
🧬 Homotrimer UMI support (majority vote & set cover)
🧪 scRNA-seq simulation (DeepConvCVAE)
📊 Visual analytics
A step forward in deduplication accuracy & benchmarking.
#UMI #scRNAseq #bioinformatics

📢 New preprint alert!
We present UMIche, a modular, open-source platform to improve UMI-based molecular quantification in bulk and scRNA-seq data.
→ Integrated pipelines
→ Monomer & homotrimer UMIs
→ Deep learning-based simulation
🔗 doi.org/10.21203/rs....

Ever torn a tendon? Our study led by @joletmimpen.bsky.social discovered changes in fibroblast and immune cell populations that occur in quadriceps tendon tears.

Read more: doi.org/10.1113/JP28...

@sarahsnelling.bsky.social
@adamcribbs.bsky.social

FlowAgent: A Modular Agent-Based System for Automated Workflow Management and Data Interpretation https://www.biorxiv.org/content/10.1101/2025.03.06.641728v1

With FlowAgent, experimental biologists can efficiently run sophisticated analyses without coding expertise, allowing bioinformaticians to prioritise high-level interpretation and innovation.

Benchmarking demonstrated that FlowAgent, powered by GPT-4o, outperforms other models in terms of speed, accuracy, and cost-efficiency, ideal for scalable and diverse bioinformatics analyses.

FlowAgent autonomously handles dependency management, tool selection, and real-time parameter optimisation. Intelligent agents continuously monitor computational performance, dataset quality, and software compatibility, providing robust quality control.

Traditional workflow management systems often require extensive programming skills, limiting usability and adaptability. FlowAgent leverages large language models (LLMs) to translate plain English instructions into structured pipelines, democratising access.

GitHub - EnteloBio/flowagent: An advanced multi-agent framework for automating complex bioinformatics workflows. An advanced multi-agent framework for automating complex bioinformatics workflows. - EnteloBio/flowagent

Numerous developments and improvements are currently underway following this initial release.
🔗 github.com/EnteloBio/fl...

FlowAgent: A Modular Agent-Based System for Automated Workflow Management and Data Interpretation Reproducibility, automation, and flexibility remain persistent challenges in bioinformatics, where complex workflows require integration of diverse computational tools, rigorous quality control, and d...

We are pleased to share our latest preprint: "FlowAgent: A Modular Agent-Based System for Automated Workflow Management and Data Interpretation". FlowAgent makes complex bioinformatics workflows accessible and adaptive using agentic #AI. #Bioinformatics www.biorxiv.org/content/10.1...

A screenshot of an X post by Paul Graham (@paulg ) posted 13 hours ago on March 7, 2025, asking which American Republican leaders are bold enough to respond to a question posed by Inna Sovsun (@InnaSovsun ). Inna Sovsun's post challenges those suggesting Ukraine give up Crimea and Donbas for peace by asking them to name a specific region in their own country they would surrender if Putin started bombing their cities.

Oooh! Oooh! I know! Mar-a-Lago.

The anchor-enhanced design demonstrated substantial improvements in data quality, particularly in detecting low-abundance transcripts and improving the transcript coverage.

The effects of adding an anchor sequence are a significantly increased number of features per cell over and above not having an anchor (Positional).

By integrating an anchor sequence before and after the UMI, we observed a significant reduction in technical variability, an increase in UMI accuracy, leading to more accurate gene expression measurements.

Turns out for droplet based single-cell methods, beads are truncated and this leads to several issues with downstream artefacts. Mainly, there is an overrepresentation of Ts in the UMI that result from truncated bead synthesis.

Enhancing single-cell transcriptomics using interposed anchor oligonucleotide sequences - Communications Biology Droplet-based sequencing is key to single-cell transcriptomics but faces challenges from bead synthesis errors. A new bead design with anchor sequences improves UMI identification, read recovery, and ...

Bit late, but first paper of 2025. 🧬Enhancing #singlecell #transcriptomics: Our recent study introduces an interposed anchor strategy to improve gene expression profiles in droplet-based single-cell sequencing analyses. www.nature.com/articles/s42...

I was just told that I have to remove “climate” from the title of an ongoing grant if I want to keep it. And publications from that grant cannot include “climate” and other forbidden words. I can’t believe I’m writing this from the United States of America. #AcademicSky

Enhancing single-cell transcriptomics using interposed anchor oligonucleotide sequences - Communications Biology Droplet-based sequencing is key to single-cell transcriptomics but faces challenges from bead synthesis errors. A new bead design with anchor sequences improves UMI identification, read recovery, and ...

Droplet-based sequencing is key to single-cell transcriptomics but faces challenges from bead synthesis errors. A new bead design with anchor sequences improves UMI identification, read recovery, and feature detection for both short- and long-read methods.

www.nature.com/articles/s42...