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UMI-tools was published in Genome Research on 18 Jan '17 (open access)

For full documentation see

Tools for dealing with Unique Molecular Identifiers

This repository contains tools for dealing with Unique Molecular Identifiers (UMIs)/Random Molecular Tags (RMTs) and single cell RNA-Seq cell barcodes. Currently there are 6 commands.

The extract and whitelist commands are used to prepare a fastq containg UMIs +/- cell barcodes for alignment.

  • whitelist:
    Builds a whitelist of the 'real' cell barcodes
    This is useful for droplet-based single cell RNA-Seq where the identity of the true cell barcodes is unknown. Whitelist can then be used to filter with extract (see below)
  • extract:
    Flexible removal of UMI sequences from fastq reads.
    UMIs are removed and appended to the read name. Any other barcode, for example a library barcode, is left on the read. Can also filter reads by quality or against a whitelist (see above)

The remaining commands, group, dedup and count/count_tab, are used to identify PCR duplicates using the UMIs and perform different levels of analysis depending on the needs of the user. A number of different UMI deduplication schemes are enabled - The recommended method is directional.

  • dedup:
    Groups PCR duplicates and deduplicates reads to yield one read per group
    Use this when you want to remove the PCR duplicates prior to any downstream analysis
  • group:
    Groups PCR duplicates using the same methods available through `dedup`.
    This is useful when you want to manually interrogate the PCR duplicates
  • count:
    Groups and deduplicates PCR duplicates and counts the unique molecules per gene
    Use this when you want to obtain a matrix with unique molecules per gene, per cell, for scRNA-Seq.
  • count_tab:
    As per count except input is a flatfile

See for a quick tutorial on the most common usage pattern.

If you want to use UMI-tools in single-cell RNA-Seq data processing, see

Important update: We now recommend the use of alevin for droplet-based scRNA-Seq (e.g 10X, inDrop etc). alevin is an accurate, fast and convenient end-to-end tool to go from fastq -> count matrix and extends the UMI error correction in UMI-tools within a framework that also enables quantification of droplet scRNA-Seq without discarding multi-mapped reads. See alevin documentation and alevin pre-print for more information

The dedup, group, and count / count_tab commands make use of network-based methods to resolve similar UMIs with the same alignment coordinates. For a background regarding these methods see:

Genome Research Publication

Blog post discussing network-based methods.


If you're using Conda, you can use:

$ conda install -c bioconda -c conda-forge umi_tools

Or pip:

$ pip install umi_tools

Or if you'd like to work directly from the git repository:

$ git clone

Enter repository and run:

$ python install

For more detail see INSTALL.rst


For full documentation see

See and for tutorials on the most common usage patterns.

To get help on umi_tools run

$ umi_tools --help

To get help on the options for a specific [COMMAND], run

$ umi_tools [COMMAND] --help


umi_tools is dependent on python>=3.5, numpy, pandas, scipy, cython, pysam, future, regex and matplotlib

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