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Published April 18, 2025 | Version v1.1
Software Open

Improving gene isoform quantification with miniQuant

  • 1. ROR icon University of Michigan–Ann Arbor

Description

miniQuant features:

  1. Optimal use of long and/or short RNA-seq reads: transcript abundance estimation that can be applied to different data scenarios: long-read-alone and hybrid (long reads + short reads) integrating the strengths of both technologies.
  2. Fast RNA-seq quantification: less than 15 minutes to analyze unaligned 40 million paired-end short reads + 5 million long reads on a standard laptop computer.
  3. Calculate novel K-value metric: a key feature of the sequence share pattern that causes particularly high abundance estimation error, allowing us to identify a problematic set of gene isoforms with erroneous quantification that researchers should take extra attention in the study.

Files

Files (15.7 MB)

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md5:0de2c063c40828441d7293a07e46153b
15.7 MB Download

Additional details

Software

Repository URL
https://github.com/Augroup/miniQuant/
Programming language
Python, C++
Development Status
Active