Trim Galore

−60%

CPU vs v0.6 — saves time, $, CO₂

N×

speed-up at --cores N · natively parallel

0deps

no Python, Java, Cutadapt, igzip, pigz

10+

years in production

What's new in v2

Same CLI, same output filenames, same report format — with a few capabilities the Perl version did not have.

01

Single binary

No Python, Perl, Cutadapt, Java, igzip, or pigz dependencies. Install via cargo install trim-galore, from bioconda, or pull a Docker image.

02

Single-pass paired-end

Both reads are processed together in one pass. No temp files, no separate adapter / quality / length validation passes.

03

Poly-G auto-detect

Trims no-signal G-runs from 2-colour instruments. Auto-enabled when the data looks 2-colour. Independent of --nextseq quality trimming.

04

Smarter adapter detection

Adapter auto-detection now runs per file (or file-pair) instead of once on the first input. BGI/DNBSEQ joins the probe set alongside Illumina, Nextera, and smallRNA.

05

Built-in FastQC

FastQC reports run in-process via the bundled fastqc-rust library. No Java, no external fastqc binary. Pass --fastqc and it just works.

// usage

One command

Defaults work for most Illumina libraries. Auto-detected adapter, Phred quality trimming, paired-end validation.

trim_galore --cores 8 sample.fastq.gz                                  # single-end
trim_galore --cores 8 --paired sample_R1.fastq.gz sample_R2.fastq.gz   # paired-end

Where next

Installation cargo, bioconda, Docker, or prebuilt binaries.

Quick start Run your first trim. Single-end, paired-end, RRBS.

User guide How quality and adapter trimming work, step by step.

Bisulfite & RRBS The biology, the strand types, and how Trim Galore handles each.

Benchmarks Performance numbers and the reasons behind them.

Migrating from v0.6.x What changed and how to update existing pipelines.