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Single cell A-to-I RNA editing




The goal of this project is to develop a method that enables detection of A-to-I editing in intronic RNA sequences in single cell data. This has never been done before and, similar to Velocity, analysis of these unspliced sequences may reveal novel cell states and state transitions. The project will conclude with a case-study applying this method to a previously published scRNA-Seq dataset.

Bash, R, Snakemake or NextFlow

scRNA-Seq, Linux, Snakemake/NextFlow, Method development

Project Stage


Avg. Hours / Week


Project Provider

Shizuka Uchida, PhD

Commitment (Months)


Spots Open


Project Lead

Henry Miller (Tentative)

Publication if successful?


Trainee authorship criteria (if applicable)

The BRN trainees will be co-authors.

NOTE: Preference will be given to trainees with demonstrated ability to implement server-side data pre-processing -- this includes familiarity with either snakemake or nextflow & working knowledge of RNA alignment and samtools.

Required Skill Assessments

Single-Cell RNA-Seq

R Programming

Linux for Bioinformatics

RNA-Seq Analysis

R for Data Science

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