FastpEdit

Fastp is a software tool designed for preprocessing sequencing data, particularly reads generated by high-throughput platforms. It aims to streamline the preparation of FASTQ data for downstream analysis by combining several common steps into a single, fast workflow. The program is widely used in genomics and transcriptomics pipelines to improve data quality before alignment, assembly, or variant calling. It supports both single-end and paired-end reads and can handle compressed input files, making it suitable for large-scale projects that generate vast amounts of data. For background concepts, see FASTQ and Illumina technology, which often serve as the starting points for preprocessing with fastp.

fastp is typically invoked as a command-line tool, often integrated into automated pipelines. A typical workflow might involve trimming adapters, filtering low-quality reads, and producing QC reports in parallel with the output of cleaned reads. Its design emphasizes speed and simplicity, allowing researchers to run comprehensive preprocessing in a single pass rather than stitching together multiple standalone utilities. See paired-end sequencing for an outline of how both reads in a pair can be processed in coordination during preprocessing.

Overview

fastp is characterized by its all-in-one approach to FASTQ preprocessing. The software is capable of: - Detecting and trimming sequencing adapters, either via explicit specification or automatic identification from the data. - Filtering and trimming reads based on quality scores, with options for sliding window approaches and minimum read length requirements. - Correcting bases in paired-end data by leveraging overlaps between read pairs to improve accuracy. - Trimming problematic sequences at the ends of reads, including specialized handling for polyG tails, a feature that helps mitigate artifacts common in certain Illumina platforms. - Generating detailed quality control metrics and reports, including HTML and JSON formats, to aid in evaluating data quality before downstream processing. - Supporting both ordinary text FASTQ inputs and compressed inputs (e.g., FASTQ.gz) and multiple output modes suitable for integration into pipelines. - Operating efficiently on large data sets through multithreading and optimized algorithms.

In practice, users feed fastp their input data, configure a few quality and trimming parameters, and receive cleaned reads along with a QC report to assess the impact of preprocessing. See input files and quality score concepts for related background.

Features

  • Automatic and explicit adapter trimming: fastp can infer adapters from the data or use user-provided adapter sequences, simplifying setup in diverse projects. See adapter terminology for more context.
  • Quality-based trimming and filtering: per-read quality filtering, sliding window trimming, and length-based filters help ensure that downstream alignments and analyses are not compromised by poor-quality bases.
  • Base correction for PE data: overlapping regions in paired-end reads can be used to correct certain mismatches, potentially improving the accuracy of downstream alignment.
  • Specialized tail trimming: polyG tail trimming addresses artifacts around the 3' ends of reads that can occur with some sequencing chemistries; polyX trimming helps remove low-complexity or biased tail sequences.
  • Comprehensive QC reporting: the HTML report provides visual summaries of read quality, base composition, GC content, and overrepresented sequences, while the JSON report captures machine-readable statistics for programmatic use.
  • Input/output flexibility: supports single-end and paired-end reads, interleaved formats, and compressed input/output to fit into various data-management setups.
  • Integration-friendly design: fastp is commonly scripted into pipelines and can produce preprocessed FASTQ files alongside a QC summary suitable for automated reporting.
  • Performance: designed to be fast and memory-efficient, leveraging multithreading to handle large-scale data without creating unnecessary bottlenecks. See multithreading concepts for related technical background.

Implementation and usage

fastp is a cross-platform, open-source tool implemented in C++. It is typically used from the command line, with a range of options to tailor preprocessing. A representative usage pattern might specify input files for the 5' and 3' reads in paired-end data, specify or let the program detect adapters, set quality thresholds, and request HTML/JSON reports. The resulting outputs consist of cleaned read files and accompanying QC reports. For context on the data formats involved, see FASTQ format and Illumina sequencing workflows.

In addition to standard usage, fastp can be configured to run in more advanced modes, such as enabling or disabling specific modules, setting thread counts, and controlling the aggressiveness of trimming. The balance between aggressive trimming and preserving informative sequence content is a practical consideration in any preprocessing step, and fastp provides a transparent set of diagnostics to guide those choices. See quality control for related topics on assessing sequencing data quality and preprocessing impact.

Adoption and impact

Since its introduction, fastp has been adopted across many genomics labs and large consortia due to its convenience and speed. By consolidating trimming, filtering, and QC into a single tool, researchers can reduce the number of dependent steps in a pipeline, simplify reproducibility, and accelerate the time from data generation to analysis. See bioinformatics workflow for broader discussions of how preprocessing tools fit into end-to-end sequencing projects.

See also