Sanger Read vs Reference — Clone Verification
Align a Sanger read to a reference and get a pass / needs-review verification report.
🌐 Nothing you paste is logged or stored — every tool is also callable via REST & MCP, and in bulk from the batch tools
Confirm that a Sanger read matches the sequence you expected. Paste a read in FASTA (or upload an .ab1 trace and its base calls are extracted for you) together with the reference template; the tool fits the read onto the reference and produces a verification report — percent identity over the region the read actually covers, how much of the reference that was, every substitution, insertion and deletion with reference coordinates and HGVS-style notation, a colored side-by-side diff, and a pass / needs-review / ambiguous-low-coverage verdict. Your data is never logged or stored, and the same verification is available via the REST API and the MCP server. It is the fast way to check a cloned construct or a mutagenesis product against its intended sequence before moving on.
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Paste (or upload) a Sanger read and a reference sequence to verify the read against the expected template.
The read is fitted onto the reference with a semi-global alignment: the read is consumed end to end while reference outside the read's footprint costs nothing, since it was never read. Every mismatch, insertion and deletion inside that footprint is called against the reference with a 1-based coordinate and HGVS-style g. notation, and the reported identity is over the footprint only — the Coverage tile is what tells you how much of the reference was actually checked. The verdict is a triage aid — a read is marked PASS at ≥99% identity with no indels, NEEDS REVIEW otherwise, and AMBIGUOUS when coverage falls below the threshold, because a PASS on a partial read would claim more than was checked. Always confirm called differences by eye on the chromatogram (in the Sanger Trace Viewer), since low-quality base calls near the read ends are the most common source of spurious mismatches.
Working on a whole construct rather than one read? Open SeqStudio — the full editor, with live feature annotation, plasmid maps, restriction and primer panels, undo/redo, multi-document tabs and GenBank / SnapGene import and export.
How to use the Sanger vs Reference tool
- 1Paste the reference (expected) sequence — trim it to just the region or junction you are checking if the read won't span the whole thing.
- 2Paste the Sanger read as FASTA, or upload an .ab1 / .abi trace to pull in its base calls.
- 3Read the verdict and coverage before the identity figure, then work through the mismatch/indel table and inspect the colored diff at each difference.
Frequently asked questions
How do I provide the read — paste or file?
Either. Paste the read as FASTA or raw text, or upload the .ab1 / .abi trace and its base calls are extracted for you. The reference is always pasted. An uploaded trace is used only for parsing and is never logged or stored.
How is the pass / needs-review verdict decided?
There are three verdicts, not two. Coverage is checked first: if the read spans less than 90% of the reference (adjustable), the verdict is AMBIGUOUS — LOW COVERAGE no matter how clean the covered part looks, because the read simply didn't reach most of what you asked about. With coverage satisfied, the read is marked PASS at 99% or higher identity with no insertions or deletions, and NEEDS REVIEW otherwise. It is a triage aid — always confirm called differences by eye on the chromatogram, since low-quality base calls near the read ends are the most common source of spurious mismatches.
What differences does the report list?
Every substitution, insertion and deletion between the read and the reference, each with a 1-based reference coordinate and HGVS-style g. notation (e.g. g.54G>A, g.54del, g.54_55ins), plus counts of mismatches, insertions and deletions and the overall percent identity.
How are the two sequences aligned?
With a fitting alignment: the read is consumed end to end, but the reference's overhanging ends are free, so a read covering only part of the reference is placed where it belongs instead of being stretched across the whole template. Percent identity is then measured over that aligned footprint alone — a short read that matches perfectly reads 100%, and how much of the reference it missed is reported separately as coverage rather than being folded into the identity figure.
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