Single-cell genomics preprocessing package

This tool is an automated pipeline for preprocessing single-cell genomics data. It is designed to take raw data (fastq files) from a variety of single-cell genomics platforms and a seqspec file as input, and output a count matrix (RNA) or a fragment file (ATAC) for downstream analysis. The seqspec files for common platforms can be found here: https://github.com/IGVF/seqspec.

Installation

Stable version

pip install precellar

Development version

pip install 'git+https://github.com/regulatory-genomics/precellar.git#egg=precellar&subdirectory=python'

Examples

10X scATAC-seq

import precellar

assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/10x_atac.yaml')
assay.add_illumina_reads('atac')
assay.update_read('atac-R1', fastq='R1.fastq.gz')
assay.update_read('atac-I2', fastq='R2.fastq.gz')
assay.update_read('atac-R2', fastq='R3.fastq.gz')
qc = precellar.align(
    assay,
    precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCh38"),
    modality="atac",
    output='fragments.tsv.zst',
    output_type='fragment',
    num_threads=32,
)
print(qc)

10X scRNA-seq

import precellar

assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/10x_rna_v3.yaml')
assay.add_illumina_reads('rna')
assay.update_read('rna-R1', fastq='R1.fastq.gz')
assay.update_read('rna-R2', fastq='R2.fastq.gz')
qc = precellar.align(
    assay,
    precellar.aligners.STAR("/data/STAR_reference/star_2.7.1"),
    modality="rna",
    output="gene_matrix.h5ad",
    output_type="gene_quantification",
    num_threads=32,
)
print(qc)

10X single-cell multiome (Gene expression + ATAC)

import precellar

assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/10x_rna_atac.yaml')

assay.add_illumina_reads('rna')
assay.update_read('rna-R1', fastq='gex_R1.fastq.gz')
assay.update_read('rna-R2', fastq='gex_R2.fastq.gz')

assay.add_illumina_reads('atac')
assay.update_read('atac-R1', fastq='atac_R1.fastq.gz')
assay.update_read('atac-I2', fastq='atac_R2.fastq.gz')
assay.update_read('atac-R2', fastq='atac_R3.fastq.gz')

rna_qc = precellar.align(
    assay,
    precellar.aligners.STAR("/data/STAR_reference/star_2.7.1"),
    modality="rna",
    output="gene_matrix.h5ad",
    output_type="gene_quantification",
    num_threads=32,
)
atac_qc = precellar.align(
    assay,
    precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCh38"),
    modality="atac",
    output='fragments.tsv.zst',
    output_type='fragment',
    num_threads=32,
)

For more information, please refer to the documentation: https://lab.kaizhang.org/precellar/.