Dot Plot Generator

The dot plot, introduced by Gibbs and McIntyre (1970) and refined by Maizel and Lenk (1981), is the fastest way to see the whole shape of a similarity between two sequences before committing to a scored alignment. Every diagonal run of dots is a stretch where the two sequences agree, so the eye reads colinearity, rearrangement, and repeats directly from the geometry.

The vocabulary is simple and powerful. A continuous diagonal is a conserved colinear region. A shifted or broken diagonal is an insertion or deletion, because one sequence gains or loses bases relative to the other. A parallel off-diagonal line is a repeat, and an anti-diagonal line is an inversion, which this tool draws in red when you enable reverse-strand matching. Comparing a sequence against itself turns the plot into a repeat finder, exposing tandem duplications and palindromic hairpins.

The single most important control is the word size. Because random short matches accumulate as background noise, raising the word length filters the plot down to genuinely significant similarity, while lowering it surfaces weaker, more-diverged relationships. This trade-off is the dot plot equivalent of a sensitivity-specificity dial, and choosing it well is what separates a readable plot from a grey smear. To reconstruct the reverse strand that inverted matches are computed against, use the reverse complement tool.

Dot plots remain a diagnostic rather than a quantitative method: they show that a similarity exists and what type it is, but they do not score it or call an optimal alignment. For whole-genome comparison a dedicated aligner is the right tool, and for the statistics that turn sequence observations into results, from composition to expression, the bioinformatics analysis service handles the full analysis with reproducible methods.