PEARS

A pipeline for finding fusions in single-cell RNA sequencing data

PEARS

Pipeline for gene-fusion searching in Rna Single-cell sequences

PEARS is a Nextflow DSL2 pipeline that detects gene fusions at single-cell resolution from 10x scRNA-seq and Visium HD spatial transcriptomics data. It combines three complementary fusion-calling approaches — FUSCIA, Flexiplex, and Arriba — and assigns cell barcodes to each detected fusion event, producing per-cell fusion calls.

Pipeline overview

  1. Reference preparation — Downloads genome FASTA and GTF annotation (or uses pre-built references).
  2. Fusion target generation — Builds search targets from a known fusions list using the reference annotation.
  3. Alignment — Aligns reads with STARsolo (chimeric-aware) and produces a BAM and single-cell count matrix.
  4. Fusion detection — Calls fusions using FUSCIA, Flexiplex, and Arriba in parallel.
  5. Formatting — Consolidates results into per-tool CSVs and a combined combined_fusions.csv. For Visium HD data, spatial bin barcodes are written to combined_fusions_spatial.csv.

Requirements

Installation

git clone https://github.com/DavidsonGroup/pears.git

Usage

Running locally:

nextflow run /path/to/pears \
  --fastq_r1 "/path/to/Reads_R1.fastq.gz" \
  --fastq_r2 "/path/to/Reads_R2.fastq.gz" \
  --known_fusions_list "known_fusions.csv" \
  --protocol "10x-3prime-v3" \
  --genome_version "GRCh38+GENCODE44" \
  --out_dir "pears_output" \
  -profile "local" \
  -resume

Running on a SLURM cluster (recommended for large datasets):

nextflow run /path/to/pears \
  --fastq_r1 "/path/to/Reads_R1.fastq.gz" \
  --fastq_r2 "/path/to/Reads_R2.fastq.gz" \
  --known_fusions_list "known_fusions.csv" \
  --protocol "10x-3prime-v3" \
  --genome_version "GRCh38+GENCODE44" \
  --out_dir "pears_output" \
  -profile "slurm" \
  -resume

Running on Visium HD spatial transcriptomics data:

nextflow run /path/to/pears \
  --fastq_r1 "/path/to/Reads_R1.fastq.gz" \
  --fastq_r2 "/path/to/Reads_R2.fastq.gz" \
  --known_fusions_list "known_fusions.csv" \
  --protocol "10x-3prime-visiumHD" \
  --genome_version "GRCh38+GENCODE44" \
  --out_dir "pears_output" \
  -profile "slurm" \
  -resume

The -resume flag allows you to continue from the last successful step if the pipeline is interrupted.

Tip: Nextflow also supports running directly from GitHub without cloning first: nextflow run DavidsonGroup/pears [arguments].

Protocol presets

--protocol sets the barcode whitelist and UMI length for the given 10x chemistry.

Preset Chemistry UMI length
10x-3prime-v2 3’ Gene Expression v2 10 bp
10x-3prime-v3 3’ Gene Expression v3/v3.1 12 bp
10x-3prime-v4 3’ Gene Expression v4 12 bp
10x-5prime-v2 5’ Gene Expression v1/v2 10 bp
10x-5prime-v3 5’ Gene Expression v3 12 bp
10x-3prime-visiumHD Visium HD spatial transcriptomics 9 bp

Key arguments

Argument Default Description
--fastq_r1 — Path to Read 1 FASTQ file(s) (gzipped).
--fastq_r2 — Path to Read 2 FASTQ file(s) (gzipped).
--known_fusions_list — CSV of known/candidate fusions to search for.
--protocol — 10x chemistry preset (see table above).
--genome_version GRCh38+GENCODE44 Reference genome to download.
--out_dir pears_output Output directory.
--discover_fusions false Discover novel fusions via Arriba in addition to known fusions.
--min_arriba_support 20000 Minimum reads for a novel Arriba fusion to be included.
--arriba_exclusion_file — Path to a gzipped Arriba blacklist (.tsv.gz) to filter likely false positives. See Arriba releases for pre-built blacklists.
--visium_bin_size 8 (Visium HD only) Bin size in microns (2, 8, or 16) for spatial barcode conversion.
--cpus 16 CPUs per process.
--memory 128 GB Memory per process.
--time 48h Wall-time limit per process.
-profile — local or slurm.

For the full argument reference see the README.

Known fusions list format

The --known_fusions_list input is a CSV with the following columns:

Column Description
fusion genes Fusion pair separated by -- (e.g. BCAS4--BCAS3).
chrom1 Chromosome of gene 1.
base1 Breakpoint position of gene 1.
strand1 Strand of gene 1 (+ or -).
chrom2 Chromosome of gene 2.
base2 Breakpoint position of gene 2.
strand2 Strand of gene 2 (+ or -).

This format is compatible with JAFFA output. Additional columns are ignored.

fusion genes,chrom1,base1,strand1,chrom2,base2,strand2,classification
BCAS4--BCAS3,chr20,50795173,+,chr17,61368327,+,HighConfidence
RPS6KB1--VMP1,chr17,59914703,+,chr17,59839768,+,HighConfidence

Output

Results are written to --out_dir:

File Description
combined_fusions.csv All tools merged: UMI counts per tool and total per (fusion, cell) pair.
combined_fusions_spatial.csv (Visium HD only) Combined fusions with SpaceRanger-format spatial barcodes (e.g. s_008um_00241_00258-1).
fuscia_fusion_calls.csv Per-cell fusion calls from FUSCIA.
flexiplex_fusion_calls.csv Per-cell fusion calls from Flexiplex.
arriba_fusion_calls.csv Per-cell fusion calls from Arriba.
STARsolo/ BAM alignment and single-cell count matrix.
arriba_out/ Arriba fusion table and per-fusion barcode files.
fusion_targets.csv Generated fusion target sequences.
nextflow_report.html Nextflow execution report.

Credits

Adapted from FUSCIA (Steven Foltz, 2019) and Flexiplex (Davidson et al., 2022).