bio-tcr-bcr-analysis-mixcr-analysis

name	bio-tcr-bcr-analysis-mixcr-analysis
description	Perform V(D)J alignment and clonotype assembly from TCR-seq or BCR-seq data using MiXCR. Use when processing raw immune repertoire sequencing data to identify clonotypes and their frequencies.
tool_type	cli
primary_tool	MiXCR

MiXCR Analysis

Complete Workflow (Recommended)

mixcr analyze generic-tcr-amplicon \
    --species human \
    --rna \
    --rigid-left-alignment-boundary \
    --floating-right-alignment-boundary C \
    input_R1.fastq.gz input_R2.fastq.gz \
    output_prefix

mixcr analyze 10x-vdj-tcr \
    input_R1.fastq.gz input_R2.fastq.gz \
    output_prefix

Step-by-Step Workflow

Step 1: Align Reads

mixcr align \
    --species human \
    --preset generic-tcr-amplicon-umi \
    input_R1.fastq.gz input_R2.fastq.gz \
    alignments.vdjca

mixcr align \
    --species human \
    --rna \
    -OallowPartialAlignments=true \
    input_R1.fastq.gz input_R2.fastq.gz \
    alignments.vdjca

Step 2: Refine and Assemble

mixcr refineTagsAndSort alignments.vdjca alignments_refined.vdjca

mixcr assemble alignments_refined.vdjca clones.clns

Step 3: Export Results

mixcr exportClones \
    --chains TRB \
    --preset full \
    clones.clns \
    clones.tsv

mixcr exportClones \
    --chains TRB \
    -cloneId -readCount -readFraction \
    -nFeature CDR3 -aaFeature CDR3 \
    -vGene -dGene -jGene \
    clones.clns \
    clones_custom.tsv

Preset Protocols

Protocol	Use Case
generic-tcr-amplicon	TCR amplicon sequencing
generic-bcr-amplicon	BCR amplicon sequencing
generic-tcr-amplicon-umi	TCR amplicon with UMIs
rnaseq-tcr	TCR extraction from bulk RNA-seq
rnaseq-bcr	BCR extraction from bulk RNA-seq
10x-vdj-tcr	10x Genomics TCR enrichment
10x-vdj-bcr	10x Genomics BCR enrichment
takara-human-tcr-v2	Takara SMARTer kit

Species Support

mixcr align --species human ...
mixcr align --species mmu ...

# Available: human, mmu, rat, rhesus, dog, pig, rabbit, chicken

Output Format

Column	Description
cloneId	Unique clone identifier
readCount	Number of reads
cloneFraction	Proportion of repertoire
nSeqCDR3	Nucleotide CDR3 sequence
aaSeqCDR3	Amino acid CDR3 sequence
allVHitsWithScore	V gene assignments
allDHitsWithScore	D gene assignments
allJHitsWithScore	J gene assignments

Quality Metrics

mixcr exportReports alignments.vdjca

# Key metrics:
# - Successfully aligned reads (>80% is good)
# - CDR3 found (>70% of aligned)
# - Clonotype count (varies by sample type)

Parse MiXCR Output in Python

import pandas as pd

def load_mixcr_clones(filepath):
    df = pd.read_csv(filepath, sep='\t')
    df = df.rename(columns={
        'readCount': 'count',
        'cloneFraction': 'frequency',
        'aaSeqCDR3': 'cdr3_aa',
        'nSeqCDR3': 'cdr3_nt'
    })
    return df

Related Skills

• vdjtools-analysis - Downstream diversity analysis
• scirpy-analysis - Single-cell VDJ integration
• repertoire-visualization - Visualize MiXCR output