Skip to content
BranchesTags

Repository files navigation

Universal Single-Cell Genomics Preprocessing package

PyPI PyPI - Downloads Continuous integration GitHub Repo stars

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'

Examples

Alignment uses the chainable FastqPipeline -> AlignmentJob -> terminal output API. See Alignment Pipeline API for complete configuration, middleware, output, QC, and migration documentation.

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-MEM2, MiniBWA, and Minimap2 indexes can be built by their aligner constructors when fasta is provided.

Gene Expression

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.FastqPipeline(assay)
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCm39-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCm39-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCm39-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)
MGI DNBelab C4 scRNA-seq v1 
import precellar

assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/dnbelabc4_rna_v1_dark.yaml')

data = precellar.examples.dnbelabc4_rna_v1()
assay.update_read('R1', fastq=data['R1'])
assay.update_read('R2', fastq=data['R2'])

rna_qc = (
    precellar.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCh38-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)

Chromatin accessibility and protein-DNA interactions

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.FastqPipeline(assay)
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCh38"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
print(atac_qc)
MGI DNBelab C4 scATAC-seq v1 
import precellar

assay = precellar.Assay('https://raw.githubusercontent.com/regulatory-genomics/precellar/refs/heads/main/seqspec_templates/dnbelabc4_atac_v1.yaml')

data = precellar.examples.dnbelabc4_atac_v1()
assay.update_read('R1', fastq=data['R1'])
assay.update_read('R2', fastq=data['R2'])

qc = (
    precellar.FastqPipeline(assay)
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCh38"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
print(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.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCm39"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
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.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("BWA_MEM2_index/Zea_mays"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
print(atac_qc)

Multi-Omics

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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCm39-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)

atac_qc = (
    precellar.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCm39"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("/data/Public/STAR_reference/refdata-gex-GRCh38-2024-A/star/"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)

atac_qc = (
    precellar.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCh38"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("/data/Public/STAR_reference/GRCm39/"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)

atac_qc = (
    precellar.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCm39"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
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.FastqPipeline(assay, modality="rna")
    .align_with(
        precellar.aligners.Star("STAR_reference/refdata-gex-GRCm39-2024-A"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.GeneQuantificationSink("gene_matrix.h5ad"))
)
print(rna_qc)

atac_qc = (
    precellar.FastqPipeline(assay, modality="atac")
    .align_with(
        precellar.aligners.BwaMem2("/data/Public/BWA_MEM2_index/GRCm39"),
        num_threads=8,
    )
    .run_sink(precellar.sinks.FragmentsSink("fragments.tsv.zst"))
)
print(atac_qc)

About

Universal Single-Cell Genomics Preprocessing package

lab.kaizhang.org/precellar/

Resources

Readme
MIT license
Activity
Custom properties

Stars

51 stars

Watchers

4 watching

Forks

3 forks
Report repository

Releases

Packages

Used by

Contributors

Languages