phredsort

phredsort is a command-line tool for sorting FASTQ reads by quality metrics.In is also possible to sort FASTA inputs when quality metrics are already present in sequence headers (using headersort subcommand).

Usage

Basic usage:

# Read from `input.fastq.gz` and write to `output.fastq.gz`
phredsort -i input.fastq.gz -o output.fastq.gz

# Read from stdin and write to stdout (default when -i/-o not specified)
zcat input.fastq.gz | phredsort | less -S

# Explicit stdin/stdout (equivalent to above)
zcat input.fastq.gz | phredsort -i - -o - | less -S

Sort sequences using pre-computed maxEE scores in headers

phredsort headersort -i input.fasta -o output.fasta --metric maxee

Sort by avgphred scores with quality filtering

phredsort headersort -i input.fastq -o output.fastq --metric avgphred --minqual 20 --maxqual 40

Sort in ascending order (lower quality first)

phredsort headersort -i input.fa -o output.fa --metric meep --ascending

Examples of supported header formats:

• Space-separated: ">seq1 maxee=2.5 size=100"
• Semicolon-separated: ">seq1;maxee=2.5;size=100"

Installation

Download compiled binary (for Linux)

wget https://github.com/vmikk/phredsort/releases/download/1.4.0/phredsort
chmod +x phredsort
./phredsort --help

Build from source

git clone --depth 1 https://github.com/vmikk/phredsort
cd phredsort
go build -ldflags="-s -w" phredsort.go
./phredsort --help

Quality metrics

phredsort supports several metrics (--metric parameter) to assess sequence quality:

1. (Back-transformed) average Phred score (avgphred)

• Properly calculated mean quality score that accounts for the logarithmic nature of Phred scores
• Converts Phred scores to error probabilities, calculates their arithmetic mean, then converts back to Phred scale
• Formula: -10 * log10(mean(10^(-Q/10)))
• More accurate than simple arithmetic mean of Phred scores, which would overestimate quality

2. Maximum expected error (maxee) (as per Edgar & Flyvbjerg, 2014)

• Sum of error probabilities for all bases in a sequence
• Formula: sum(10^(-Q/10))
• Higher values indicate lower quality
• Depends on sequence length (longer sequences tend to have higher MaxEE)

3. Maximum expected error percentage (meep)

• MaxEE standardized by sequence length
• Represents expected number of errors per 100 bases
• Formula: (MaxEE * 100) / sequence_length
• Higher values indicate lower quality
• Allows fair comparison between sequences of different lengths

4. Low quality base count (lqcount)

• Number of bases below specified quality threshold
• Useful for binned quality scores (e.g., data from Illumina NovaSeq platform)
• Counts bases with Phred score < threshold (default: 15)
• Higher values indicate lower quality

5. Low quality base percentage (lqpercent)

• Percentage of bases below quality threshold
• Formula: (lqcount * 100) / sequence_length
• Higher values indicate lower quality
• Normalizes low-quality base count by sequence length