Most ECS pipelines focus on clean error-corrected reads.

What happens after variant calling is often ad hoc.

MutSeqR picks up there for mutation frequency modeling, spectrum analysis, & benchmark dose estimation across ECS platforms.

More detail here:

🔗 blog.fulcrumgenomics.com/p/mutseqr-op...

MutSeqR offers variant filtering, mutation frequency analysis, dose-response modeling, and spectrum analysis, all in a transparent, reproducible framework.

📄 Paper: doi.org/10.1093/bioa...
💻 Code: github.com/EHSRB-BSRSE-Bioinformatics/MutSeqR

#OpenScience #Genomics

ICYMI: Last week we announced MutSeqR, an open-source R package for error-corrected sequencing analysis, co-authored by our own Clint Valentine with Health Canada and U Ottawa.

It brings much-needed standardization to genetic toxicology research.

🧬 🖥️ blog.fulcrumgenomics.com/p/mutseqr-op...

MutSeqR offers an R-based framework for ECS data analysis:
→ variant filtering
→ mutation frequency + dose-response modeling
→ benchmark dose estimation
→ spectrum + signature analysis
→ reproducible visualization tools

Openly available at 🔗 github.com/EHSRB-BSRSE-Bioinformatics/MutSeqR

Proud to share that our own Clint Valentine co-authored MutSeqR, an open-source R package for analyzing error-corrected sequencing (ECS) data.
Developed with Health Canada & U Ottawa, it helps bring consistency to genetic safety research.
🔗 doi.org/10.1093/bioa...
#Genomics #OpenSource #MutSeqR 🧬🖥️

💻 MutSeqR is open source and available on GitHub:

MutSeqR provides a comprehensive R-based framework for analyzing error-corrected sequencing (ECS) data, supporting mutation frequency modeling, benchmark dose estimation, and mutation spectrum analysis.

🧬 Explore the latest from Bioinformatics Advances: “MutSeqR: An open-source R package for standardized analysis of error-corrected next-generation sequencing data in genetic toxicology.” 

Full article available: https://doi.org/10.1093/bioadv/vbaf265