Fastp runs quality control and adapter trimming in a single step, producing JSON output that MultiQC aggregates natively. GenXflo connects it to your aligner and downstream tools on one canvas and exports a reproducible Nextflow pipeline.
Fastp replaces both FastQC and a separate trimming tool in a single step. It produces filtered reads alongside a JSON QC report that MultiQC reads directly. FastQC, Fastp, your aligner of choice, and MultiQC are all pre-configured in GenXflo.
Initial raw read check
QC, trimming, JSON output
HISAT2, STAR, BWA, or Bowtie2
Aggregated QC report
The aligner node is swappable. Connect HISAT2, STAR, BWA, or Bowtie2 to Fastp on the canvas without changing any other connection.
Both Fastp and BBDuk remove adapter sequences and quality-trim reads. The practical difference is that Fastp combines QC reporting with trimming in a single pass, writing a JSON file that MultiQC reads natively. This removes the need for a separate FastQC step before trimming if the Fastp JSON report is sufficient for your QC review.
BBDuk offers more granular control over k-mer-based adapter matching and contaminant filtering, which is useful when your adapter sequences are non-standard or when you need to filter reads against a custom contaminant reference. For most standard Illumina library preparations with known adapter sequences, Fastp's automatic adapter detection and per-read quality sliding window trimming cover the same ground with less configuration.
Both are in the GenXflo library. Fastp is simpler to configure for standard Illumina libraries with automatic adapter detection and produces a JSON QC report that MultiQC reads natively. BBDuk offers more control over k-mer-based matching and contaminant filtering. For most RNA-seq and DNA sequencing experiments with standard adapters, Fastp requires less configuration and integrates more cleanly with MultiQC.
Yes. MultiQC supports Fastp JSON output directly. In GenXflo, the Fastp JSON files route to MultiQC through a canvas channel connection, so every sample's trimming statistics appear in the final aggregated report without any manual file collection.
HISAT2, STAR, BWA, and Bowtie2 are all in the GenXflo library. Any of them connect to the Fastp trimmed FASTQ output on the canvas. GenXflo validates the file type compatibility at the connection point before generating any code.