# Quality Trim Sequences

at least 2 cores/threads available
paired-end fastq sequence files gzip recommended
- sample names: a-z 0-9 . _ - case insensitive
- forward: _F .F .1 _1 _R1_001 .R1_001 _R1 .R1
- reverse: _R .R .2 _2 _R2_001 .R2_001 _R2 .R2
- fastq extension: .fq .fastq case insensitive

Raw sequences are not suitable for downstream analyses. They have sequencing adapters, index sequences, regions of poor quality, etc. The first step of any genetic sequence analyses is to remove these adapters and trim poor quality data. You can remove adapters, remove duplicates, deconvolve, and quality trim sequences using the qc module:

usage
harpy qc OPTIONS... INPUTS...

example
harpy qc --threads 20 -a auto Sequences_Raw/ 

# Running Options

In addition to the common runtime options , the qc module is configured using these command-line arguments:

argument	short name	default	description
`INPUTS`			required Files or directories containing input FASTQ files
`--deconvolve`	`-c`		Resolve barcode clashes between reads from different molecules
`--deconvolve-params`	`-p`	`21,40,3,0`	Accepts the QuickDeconvolution parameters for `k`,`w`,`d`,`a`, in that order
`--deduplicate`	`-d`		Identify and remove PCR duplicates
`--extra-params`	`-x`		Additional fastp arguments, in quotes
`--ignore-bx`		false	Ignore parts of the workflow specific to linked-read sequences
`--min-length`	`-n`	`30`	Discard reads shorter than this length
`--max-length`	`-m`	`150`	Maximum length to trim sequences down to
`--trim-adapters`	`-a`		Detect and remove adapter sequences recommended

By default, this workflow will only quality-trim the sequences.

# deduplicate reads not recommended

You can opt-in to have fastp deduplicate optical (PCR) duplicates. It's generally not recommended to perform deduplication during quality-checking, as the align workflows use the linked-read barcode to more accurately tag reads as duplicates.

# deconvolve reads conditionally recommended

You can opt-in to resolve situations where reads from different molecules have the same barcode (see deconvolve ). Performing deconvolution during the quality-checking stage of ones work would be most useful for assembly and metassembly workflows, but might hinder variant-detection workflows.

# trimming adapters recommended

You can opt-in to find and remove adapter content in sequences.

accepts auto for automatic adapter detection and removal
accepts a FASTA file of adapter sequences

example FASTA file of adapters
>Illumina TruSeq Adapter Read 1
AGATCGGAAGAGCACACGTCTGAACTCCAGTCA
>Illumina TruSeq Adapter Read 2
AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
>polyA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA

In the event you need the forward and reverse reads trimmed down to different read lengths, this can be achieved by setting -m (--max-length) to the length you want the forward reads trimmed down to (e.g. -m 125), then specify an extra fastp parameter with -x "--max_len2 VAL" to set the maximum length of the reverse reads to VAL, e.g. -x "--max_len2 130". In practice that would look like:

harpy qc -m 150 -x "--max_len2 125" -a data/fastq/

# QC Workflow

Fastp is an ultra-fast all-in-one adapter remover, deduplicator, and quality trimmer. Harpy uses it to remove adapters, low-quality bases, and trim sequences down to a particular length (default 150bp). Harpy uses the fastp overlap analysis to identify adapters for removal and a sliding window approach (--cut-right) to identify low quality bases. The workflow is quite simple.

graph LR
    subgraph Inputs
        F[FASTQ files]:::clean
    end
    Inputs-->A:::clean
    A([fastp]) --> B([count barcodes]):::clean
    A-->|--deconvolve|C([QuickDeconvolution]):::clean
    style Inputs fill:#f0f0f0,stroke:#e8e8e8,stroke-width:2px
    classDef clean fill:#f5f6f9,stroke:#b7c9ef,stroke-width:2px

The default output directory is QC with the folder structure below. Sample1 and Sample2 are generic sample names for demonstration purposes. The resulting folder also includes a workflow directory (not shown) with workflow-relevant runtime files and information.

QC/
├── Sample1.R1.fq.gz
├── Sample1.R2.fq.gz
├── Sample2.R1.fq.gz
├── Sample2.R2.fq.gz
├── reports
│   ├── Sample1.html
│   ├── Sample2.html
│   ├── summary.bx.valid.html
│   └── trim.report.html
└── logs
    ├── err
    │   ├── Sample1.log
    │   └── Sample2.log
    └── json
        ├── Sample1.fastp.json
        └── Sample2.fastp.json

item	description
`*.R1.fq.gz`	quality trimmed forward reads of the samples
`*.R1.fq.gz`	quality trimmed reverse reads of the samples
`logs/`	all debug/diagnostic files that aren't the trimmed reads `fastp` creates
`logs/err`	what fastp prints to `stderr` when running
`reports/*.html`	interactive html reports `fastp` creates from quality trimming
`reports/trim.report.html`	a report generated by `multiqc` summarizing the quality trimming results
`reports/summary.bx.valid.html`	a report detailing valid vs invalid barcodes and the segments causing invalidation
`logs/json`	json representation of the data `fastp` uses to create the html reports

By default, Harpy runs fastp with these parameters (excluding inputs and outputs):

fastp --trim_poly_g --cut_right

The list of all fastp command line options is quite extensive and would be cumbersome to print here. See the list of options in the fastp documentation.

These are the summary reports Harpy generates for this workflow. You may right-click the images and open them in a new tab if you wish to see the examples in better detail.

fastp reports

Trimming and QC

BX validation

Reports of all QC activities performed by fastp (fastp creates this)

Aggregates the metrics FASTP generates for every sample during QC.

Reports the number of valid/invalid barcodes in the sequences and the segments contributing to invalidation.