Note: You might also want to use DeepBE, for a larger variety of base editor guide RNA recommendations and efficiency predictions.
The Load Example button is able to replicate the example inputs shown in this help page for quick testing of the DeepBaseEditor web server. Simply click the Load Example button then press Submit Job to obtain an example results page.
This model takes nine input formats, each of which resolves to the target sequences it scores: FASTA, Gene Symbol, NMID, Ensembl ID, HGNC ID, Genomic Position, Edit Sequence (an unedited/edited pair), ClinVar ID and COSMIC ID. Choosing one under Input Format shows the fields it needs and hides the rest; FASTA is taken either as text or as a file upload. You may use the Load Example button to fill in example inputs for each input type.
When uploading files, press the [+] button to add files. Uploaded files can be cleared by pressing either of the checkmark buttons.
The window scored is the one the selected model reads, and the two models read different widths: 26 bp for the Adenine Base Editor (ABE) — 3 bp of 5' flank, the 20 bp protospacer and its NGG PAM — and 25 bp for the Cytosine Base Editor (CBE), which carries one base less of 5' flank. That is what the FASTA fields ask for: at least 26 bp under ABE and 25 bp under CBE, below which a sequence holds no whole target site. Both models deaminate protospacer positions 3 to 10, so the extra base of flank moves where the window sits in the row and not where it sits in the protospacer.
A gene identifier is looked up in Human (GENCODE v50 on GRCh38) or Mouse (GENCODE M39 on GRCm39). The selector appears with the four gene formats, and it is offered wherever the genome-wide off-target search offers Mouse, so a run that screens against the mouse genome can design in mouse as well.
A mouse symbol from an older nomenclature resolves to the current one and the job log states the substitution — Olfr1 designs against Or1e16. Whichever of the four gene formats is chosen, Mouse replaces the identifier box with Enter Mouse Gene Name or ID, which takes a mouse symbol or a mouse Ensembl gene ID. ClinVar ID and COSMIC ID carry no species selector: both are human variant databases, and both resolve against the human reference.
Olfr1
Or1e16
Cloning Vector decides whether the results carry an ordering-ready oligo pair, and it is set to SpCas9 / lentiGuide-Puro (BbsI or BsmBI) by default. Every candidate then gains Oligo (forward) and Oligo (reverse), in the results table and in the downloadable files alike: the two strands that anneal into the digested vector, each presenting its own 4 nt 5' overhang — CACC on the forward strand, AAAC on the reverse. The guide between them is written (G/g)N19, position 1 replaced by the G the U6 promoter transcribes from.
Oligo (forward)
Oligo (reverse)
CACC
AAAC
Setting the vector to None (No Oligo Output) leaves both columns out rather than blank. The four overhang fields — Forward 5′, Reverse 5′, Forward 3′ and Reverse 3′ — override what the vector supplies; left blank, each takes the vector's own. A guide carrying anything outside A, C, G and T gives an empty pair, because there is nothing orderable to write.
The Off-target score (higher = less specific) column is a mismatch-tolerance score, not a count of sites in a genome. It asks a narrower question than its name suggests: for this guide, how much activity would survive a single mismatch, averaged over every single-mismatch variant of the protospacer. A guide that tolerates mismatches well is more likely to engage a site it was not aimed at, and a base editor that engages deaminates there, which is why a higher number is the worse one.
It comes from the SpCas9 cutting frequency determination (CFD) table of Doench, Fusi et al. (2016), so it needs no genome and costs nothing beyond the on-target prediction. The table is indexed over the 20 nt protospacer and takes no PAM, so it describes the RNA-DNA duplex readout the two heads share: a D10A nickase forms the same R-loop over the same 20 nt spacer and the same NGG, and what differs between ABE and CBE is the deamination that follows, which the model reports as its outcome proportions. It cannot tell you where an off-target is, and it does not know whether any of those variants occurs in your genome at all.
For that, set Genome-wide off-target search to Human or Mouse. That search adds one Genome-wide specificity (higher = more specific) column, which runs the other way round: there, higher is better. Every site it finds is condensed into that single number; the individual loci are not listed, so no chromosome, coordinate or strand for them reaches the table. The two are different measurements and both may appear. The sites that search finds are scored on the same table, so the two columns differ only in the question they answer -- one guide against every single-mismatch variant of itself, one guide against the sites a genome really holds -- and never in how a mismatch is weighed.
Genome-search scoring is where that last clause stops holding. The CFD table knows which base was swapped for which, and was fitted on SpCas9 with an NGG PAM; the MIT position weights (Hsu et al. 2013) know only how tolerant each position is, and were fitted across nucleases rather than on one. Neither is a superset of the other. Leaving the setting on CFD only is the behaviour described above; choosing CFD and MIT adds a second Genome-wide specificity, MIT (higher = more specific) column, aggregated from the same search over the same sites, so the two readings can be compared directly on the guides you are choosing between. The choice applies to the genome search alone -- averaged over a complete single-mismatch panel the MIT weights return one number for every guide of a given length, which is a constant rather than a measurement, so the genome-free column is always the table's.
The results initially show a summary of the optimal guide RNA sequences for the input sequences. The base editor efficiency is the key metric here.
The summary can be visualized more clearly by clicking on each row of the table.
Click the ID in each row to view all detailed base edit outcome sequences as well as DeepBaseEditor scores and base editor proportions of each outcome.
The Download Results button is able to download the results as a ZIP file.
Cut site (1-based in the target sequence) is the position three bases from the PAM, which is where the Cas9 domain this editor is built on acts. A base editor carries a nickase rather than a nuclease, so it nicks there rather than cutting both strands, and the base it changes is inside the deamination window rather than at that position; the column is there so a candidate can be placed against the sequence it came from.
Cut site (1-based in the target sequence)
The following example interactive outputs are available for reference:
If you have any questions, bug reports, or suggestions, please do not hesitate to contact us through the Support page.
