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.
pip install precellar
pip install 'git+https://github.com/regulatory-genomics/precellar.git#egg=precellar&subdirectory=python'
Each example dataset below contains approximately 2.5 million fastq records.
Note
You need to change the paths to the reference genome in the examples below.
The reference genome should be downloaded and indexed before running the examples.
STAR genome index for human and mouse can be downloaded from here.
BWA genome index can be build using the make_bwa_index function.
10x scRNA-seq v3
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/10x_rna_v3.yaml')
data = precellar.examples.txg_rna_v3()
assay.add_illumina_reads('rna')
assay.update_read('rna-R1', fastq=data['R1'])
assay.update_read('rna-R2', fastq=data['R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("STAR_reference/refdata-gex-GRCm39-2024-A"),
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)sci-RNA-seq3
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/sci_rna_seq3.yaml')
data = precellar.examples.sci_rna_seq3()
assay.update_read('R1', fastq=data['R1'])
assay.update_read('R2', fastq=data['R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("STAR_reference/refdata-gex-GRCm39-2024-A"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)MARS-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/mars_seq.yaml')
data = precellar.examples.mars_seq()
assay.add_illumina_reads(modality='rna')
assay.update_read('rna-R1', fastq=data['R1'])
assay.update_read('rna-R2', fastq=data['R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("STAR_reference/refdata-gex-GRCm39-2024-A"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)10x scATAC-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/10x_atac.yaml')
data = precellar.examples.txg_atac()
assay.add_illumina_reads('atac', forward_strand_workflow=True)
assay.update_read('atac-I2', fastq=data['I2'])
assay.update_read('atac-R1', fastq=data['R1'])
assay.update_read('atac-R2', fastq=data['R2'])
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCh38"),
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_qc)dscATAC-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/dscATAC.yaml')
data = precellar.examples.dsc_atac()
assay.update_read('R1', fastq=data['R1'])
assay.update_read('R2', fastq=data['R2'])
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCm39"),
modality="atac",
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_qc)scifi-ATAC-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/scifi_atac.yaml')
data = precellar.examples.scifi_atac()
assay.update_read('I2', fastq=data['I2'])
assay.update_read('R1', fastq=data['R1'])
assay.update_read('R2', fastq=data['R2'])
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("BWA_MEM2_index/Zea_mays"),
modality="atac",
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_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')
data = precellar.examples.txg_multiome()
assay.add_illumina_reads('rna')
assay.update_read('rna-R1', fastq=data['rna-R1'])
assay.update_read('rna-R2', fastq=data['rna-R2'])
assay.add_illumina_reads('atac', forward_strand_workflow=True)
assay.update_read('atac-I2', fastq=data['atac-I2'])
assay.update_read('atac-R1', fastq=data['atac-R1'])
assay.update_read('atac-R2', fastq=data['atac-R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("STAR_reference/refdata-gex-GRCm39-2024-A"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCm39"),
modality="atac",
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_qc)SHARE-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/share_seq.yaml')
data = precellar.examples.share_seq()
assay.update_read('rna-I1', fastq=data['rna-I1'])
assay.update_read('rna-R1', fastq=data['rna-R1'])
assay.update_read('rna-R2', fastq=data['rna-R2'], min_len=10, max_len=10)
assay.update_read('atac-I1', fastq=data['atac-I1'])
assay.update_read('atac-R1', fastq=data['atac-R1'])
assay.update_read('atac-R2', fastq=data['atac-R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("/data/Public/STAR_reference/refdata-gex-GRCh38-2024-A/star/"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)
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=8,
)
print(atac_qc)SNARE-seq
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/snare_seq.yaml')
data = precellar.examples.snare_seq()
assay.update_read('rna-R1', fastq=data['rna-R1'])
assay.update_read('rna-R2', fastq=data['rna-R2'])
assay.update_read('atac-I1', fastq=data['atac-I1'])
assay.update_read('atac-R1', fastq=data['atac-R1'])
assay.update_read('atac-R2', fastq=data['atac-R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("/data/Public/STAR_reference/GRCm39/"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCm39"),
modality="atac",
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_qc)Droplet Paired-Tag
import precellar
assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/droplet_paired_tag.yaml')
data = precellar.examples.droplet_paired_tag()
assay.add_illumina_reads('rna')
assay.update_read('rna-R1', fastq=data['rna-R1'])
assay.update_read('rna-R2', fastq=data['rna-R2'])
assay.add_illumina_reads('atac')
assay.update_read('atac-I2', fastq=data['atac-I2'])
assay.update_read('atac-R1', fastq=data['atac-R1'])
assay.update_read('atac-R2', fastq=data['atac-R2'])
rna_qc = precellar.align(
assay,
precellar.aligners.STAR("STAR_reference/refdata-gex-GRCm39-2024-A"),
modality="rna",
output="gene_matrix.h5ad",
output_type="gene_quantification",
num_threads=8,
)
print(rna_qc)
atac_qc = precellar.align(
assay,
precellar.aligners.BWAMEM2("/data/Public/BWA_MEM2_index/GRCm39"),
modality="atac",
output='fragments.tsv.zst',
output_type='fragment',
num_threads=8,
)
print(atac_qc)For more information, please refer to the documentation: https://lab.kaizhang.org/precellar/.