GeneSweep

Sweep reference genes across hundreds of genomes at once: presence, identity, coverage and mutations. Everything runs in your browser, no files are uploaded anywhere.

1. Reference gene(s), FASTA (maximum 10,000 sequences)

Each FASTA record is treated as a separate reference sequence (minimum 30 bp). Use an annotated gene/CDS FASTA for a whole-genome gene set, not a single whole-chromosome record. Total reference sequence length is limited to 12 Mb and any one reference record to 100,000 bp for browser safety. The 10,000-record limit is an input limit, not a guarantee that every large reference-by-isolate workload will finish quickly. Start with smaller batches and monitor runtime.

2. Genome files (select many, .fasta .fa .fna, .gz works)

3. Genome order list (optional, .txt)

One exact genome file name per line, with extension (for example isolate_01.fasta). Results, CSV and FASTA will follow this order. Files not in the list go last. Names in the list with no uploaded file appear as Missing.

Min identity %

Min coverage %

Max E-value

Keep only isolates that carry all reference gene (applies to fasta file) Maximize matches (relaxed search down to 60% identity, slower) Build a multiple sequence alignment of the matched isolates for each gene (optional, tick before running)

Method Order isolates by tree

Reference is a coding sequence (classify point mutations as synonymous, missense or nonsense, and indels as frameshift or in-frame) Join gene pieces found at different places in a genome (combined coverage, like BLAST)

Advanced scoring and seed settings

Match score

Mismatch score

Gap penalty

Seed length (6-12)

Two-hit window

X-drop

Min ungapped score

Match must be positive, mismatch and gap negative. Shorter seeds find more distant genes but run slower.
X-drop: how far the score may fall below its best value before an extension stops. Higher tolerates longer bad stretches but is slower.
Min ungapped score: the score a gap-free stretch needs to be kept for full alignment. Lower is more sensitive but gives more false leads.

Genome	Gene	Status	Identity %	Coverage %	Contig	Start	End	Strand	Copies	Bitscore	E-value	Variants	Truncation	Pieces