MiXCR is a universal software for fast and accurate analysis of raw T- or B- cell receptor repertoire sequencing data.
Easy to use. Default pipeline can be executed without any additional parameters (see Usage section)
TCR and IG repertoires
Following species are supported out-of-the-box using built-in library:
- rat (only TRB and TRA)
- ... several new species will be available soon
Efficiently extract repertoires from most of (if not all) types of TCR/IG-containing raw sequencing data:
- data from all specialized RepSeq sample preparation protocols
- single-cell data
Has optional CDR3 reconstruction step, that allows to recover full hypervariable region from several disjoint reads. Uses sophisticated algorithms protecting from false-positive assemblies at the same time having best in class efficiency.
Assemble clonotypes, applying several error-correction algorithms to eliminate artificial diversity arising from PCR and sequencing errors
Clonotypes can be assembled based on CDR3 sequence (default) as well as any other region, including full-length variable sequence (from beginning of FR1 to the end of FR4)
Provides exhaustive output information for clonotypes and per-read alignments:
- nucleotide and amino acid sequences of all immunologically relevant regions (FR1, CDR1, ..., CDR3, etc..)
- identified V, D, J, C genes
- nucleotide and amino acid mutations in germline regions
- variable region topology (number of end V / D / J nucleotide deletions, length of P-segments, number of non-template N nucleotides)
- sequencing quality scores for any extracted sequence
- several other useful pieces of information
Completely transparent pipeline, possible to track individual read fate from raw fastq entry to clonotype. Several useful tools available to evaluate pipeline performance: human readable alignments visualization, diff tool for alignment and clonotype files, etc...
Installation / Download
Using Homebrew on Mac OS X or Linux (linuxbrew)
brew install milaboratory/all/mixcr
to upgrade already installed MiXCR to the newest version:
brew update brew upgrade mixcr
Manual install (any OS)
- download latest stable MiXCR build from release page
- unzip the archive
- add resulting folder to your
- or add symbolic link for
mixcrscript to your
- or use MiXCR directly by specifying full path to the executable script
- or add symbolic link for
- Any OS with Java support (Linux, Windows, Mac OS X, etc..)
- Java 1.8 or higher
Enriched RepSeq Data
Here is a very simple usage example that will extract repertoire data (in the form of clonotypes list) from raw sequencing data of enriched RepSeq library:
mixcr align -r log.txt input_R1.fastq.gz input_R2.fastq.gz alignments.vdjca mixcr assemble -r log.txt alignments.vdjca clones.clns mixcr exportClones clones.clns clones.txt
this will produce a tab-delimited list of clones (
clones.txt) assembled by their CDR3 sequences with extensive information on their abundances, V, D and J genes, mutations in germline regions, topology of VDJ junction etc.
Repertoire extraction from RNA-Seq
MiXCR is equally effective in extraction of repertoire information from non-enriched data, like RNA-Seq or WGS. This example illustrates usage for RNA-Seq:
mixcr align -p rna-seq -r log.txt input_R1.fastq.gz input_R2.fastq.gz alignments.vdjca mixcr assemblePartial alignments.vdjca alignment_contigs.vdjca mixcr assemble -r log.txt alignment_contigs.vdjca clones.clns mixcr exportClones clones.clns clones.txt
MiXCR pipeline is very flexible, and can be applied to raw data from broad spectrum of experimental setups. For detailed description of MiXCR features and options please see documentation.
Detailed documentation can be found at https://mixcr.readthedocs.io/
If you haven't found the answer to your question in the docs, or have any suggestions concerning new features, feel free to create an issue here, on GitHub, or write an email to email@example.com .
- Maven 3 (https://maven.apache.org/)
To build MiXCR from source:
git clone https://github.com/milaboratory/mixcr.git
Refresh git submodules
git submodule update --init --recursive
Run build script. First build may take several minuties to download sequences for built-in V/D/J/C gene libraries from NCBI.
Copyright (c) 2014-2015, Bolotin Dmitry, Chudakov Dmitry, Shugay Mikhail (here and after addressed as Inventors) All Rights Reserved
Permission to use, copy, modify and distribute any part of this program for educational, research and non-profit purposes, by non-profit institutions only, without fee, and without a written agreement is hereby granted, provided that the above copyright notice, this paragraph and the following three paragraphs appear in all copies.
Those desiring to incorporate this work into commercial products or use for commercial purposes should contact the Inventors using one of the following email addresses: firstname.lastname@example.org, email@example.com
IN NO EVENT SHALL THE INVENTORS BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE, EVEN IF THE INVENTORS HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
THE SOFTWARE PROVIDED HEREIN IS ON AN "AS IS" BASIS, AND THE INVENTORS HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. THE INVENTORS MAKES NO REPRESENTATIONS AND EXTENDS NO WARRANTIES OF ANY KIND, EITHER IMPLIED OR EXPRESS, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, OR THAT THE USE OF THE SOFTWARE WILL NOT INFRINGE ANY PATENT, TRADEMARK OR OTHER RIGHTS.
Dmitriy A. Bolotin, Stanislav Poslavsky, Igor Mitrophanov, Mikhail Shugay, Ilgar Z. Mamedov, Ekaterina V. Putintseva, and Dmitriy M. Chudakov. "MiXCR: software for comprehensive adaptive immunity profiling." Nature methods 12, no. 5 (2015): 380-381.
Dmitriy A. Bolotin, Stanislav Poslavsky, Alexey N. Davydov, Felix E. Frenkel, Lorenzo Fanchi, Olga I. Zolotareva, Saskia Hemmers, Ekaterina V. Putintseva, Anna S. Obraztsova, Mikhail Shugay, Ravshan I. Ataullakhanov, Alexander Y. Rudensky, Ton N. Schumacher & Dmitriy M. Chudakov. "Antigen receptor repertoire profiling from RNA-seq data." Nature Biotechnology 35, 908–911 (2017)
Files referenced in original paper
Can be found here.