Fast sequence statistics for FASTA/FASTQ files — N50, GC%, length distributions and more
Project description
seqstats
Fast sequence statistics for FASTA and FASTQ files — works on plain or gzipped inputs, no dependencies.
file seqs total_bp gc% mean_len min_len max_len N50 N90
-----------------------------------------------------------------------------------------------------------------
GRCh38.primary_assembly.fa 194 3,088,286,401 40.93 15,918,992 970 248,956,422 153,373,213 40,103,529
SRR10045678_1.fastq.gz 10000000 1,510,000,000 50.21 151.0 151 151 151 151
Install
pip install seqstatx
Or for development:
git clone https://github.com/perhapsstrawberries/seqstats.git
cd seqstats
pip install -e .
Usage
# single file
seqstatx genome.fa
# multiple files, gzipped FASTQ
seqstatx sample1.fastq.gz sample2.fastq.gz
# TSV output for downstream parsing
seqstatx --tsv *.fa > stats.tsv
# pipe to column for alignment
seqstatx --tsv *.fastq.gz | column -t
Metrics
| Column | Description |
|---|---|
seqs |
Number of sequences / reads |
total_bp |
Total base pairs |
gc% |
GC content (%) |
mean_len |
Mean sequence length |
min_len / max_len |
Shortest / longest sequence |
N50 |
50% of total assembly is in sequences ≥ this length |
N90 |
90% of total assembly is in sequences ≥ this length |
Supported formats
| Extension | Format |
|---|---|
.fa .fna .fasta |
FASTA |
.fq .fastq |
FASTQ |
.fa.gz .fastq.gz etc. |
gzipped variants |
Why
Existing tools (seqkit, seqtk) are great but require installation of compiled binaries.
seqstats is pure Python 3.10+, zero dependencies, pip-installable from any HPC or Conda environment.
License
MIT
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