On genomic interval notation
Intervals are one of the most common data abstractions used in genome informatics, along with strings and graphs. DNA has an intricate dynamic three-dimensional structure, but for many bioinformatics applications we can get away with ignoring this level of detail and representing the molecule instead as a static linear sequence of symbols. Genomic features—such as genes or transposable elements—are then annotated as subsequences of the larger complete sequence, much like an interval on a discrete number line.
The most popular data formats for encoding sequence annotations (GFF3, BED, GTF) all use a very similar convention. The location of a feature is designated by three values: some kind of label or identifier specifying the precise molecule on which the feature resides (such as Chr1 or Scaff17468), and two integers representing the start and end positions of the feature on that molecule. These values are stored in tab-delimited plain text, along with various other values and metadata.
There are, however, some substantial differences between "the big three" formats.
BED and GTF were designed for very specific use cases (visualization and gene prediction, respectively), whereas GFF3 was designed as a generalized solution for genome annotation.
BED allows for a single level of feature decomposition (a feature can be broken up into blocks) and GTF supports two levels (exons can be grouped by
transcript_id, and transcripts grouped by
gene_id), while GFF3 supports an arbitrary number of levels (parent/child relationships defined by
Parent attributes specify a directed acyclic graph of features).
Perhaps the most important difference is the notation these formats use to encode genomic intervals: that is, which two integers are used to specify the location of the interval? GFF3 and GTF both inherited, through their common heritage with older GFF variants, 1-based indexing and closed interval notation. BED on the other hand uses 0-based indexing and half-closed interval notation. Consider the DNA sequence below.
1 2 3 4 5 6 7 <-- GFF3 style | | | | | | | G A T T A C A | | | | | | | 0 1 2 3 4 5 6 <-- BED style
Using 1-based indexing and closed interval notation a la GFF3, the interval containing the subsequence
ATTA would be represented as
With BED's 0-based indexing and half-closed interval notation, the same subsequence would be represented as
Confused yet? Don't worry: off-by-one errors with interval arithmetic are very common in bioinformatics, striking newcomers and old-timers alike.
An alternative and useful way to conceptualize the BED-style notation is to shift the indices slightly so that they correspond to the spaces between nucleotides, rather than the nucleotides themselves. Then, the two integers defining an interval are the ones that bound the nucleotides in question.
G A T T A C A | | | | | | | | 0 1 2 3 4 5 6 7
So, the big question is: are there any compelling reasons to choose one convention over the other? Or is it simply a matter of preference?
Until very recently, my opinion has been that it's primarily a matter of preference. For a variety of other reasons, I have long favored the GFF3 format over any of the alternatives. Leveraging the Sequence Ontology and supporting parent/child relationships provides a more flexible, comprehensive, and consistent solution for genome annotation than any of GFF3's tab-delimited relatives. And counting nucleotides starting from 1 never really felt unnatural, at least from the perspective of a biologist.
But I'm now convinced that BED-style interval notation is indisputably superior to GFF-style interval notation. Consider the following.
- One of the most widely cited benefits of BED-style notation is that interval length calculations are much simpler:
end - startrather than
end - start + 1. Interval overlap calculations enjoy the same benefit:
min(a.end, b.end) - max(a.start, b.start)instead of
min(a.end, b.end) - max(a.start, b.start) + 1. In terms of performance, I doubt removing these extra operations will make much of a difference for the vast majority of bioinformatics software. There is a lot to be gained by making code cleaner, simpler, and easier to read, though. It's important to optimize code for human comprehension whenever possible, and removing superfluous
-1s can go a long way in this regard.
- When taking the reverse complement of a sequence, the interval
[length - end, length - start), rather than
[length - end + 1, length - start + 1). And honestly, the list of cases where the choice of notation makes these pesky
-1s disappear keeps going and going, so I'll just leave it at that.
- When splitting a sequence into, for example, 100kb chunks, the BED-style notation gives much cleaner-looking boundaries:
[100000, 200000), [200000, 300000)instead of
[100001, 200000], [200001, 300000]or
[100000, 199999], [200000, 299999].
- Another compelling argument is that most programming languages utilize 0-based indexing, so using GFF-style notation requires care on the part of the programmer to make the ajustments herself when performing interval/range operations, such as accessing a DNA subsequence stored as a string.
The BED-style notation leads to very clean C-style loops (
for(int i = start; i < end; i++)), and ranges and slices in Python use the same convention. Back in the 80s, before the computer science community had settled on 0-based indexing, renowned computer scientist Edsger Dijkstra's argument for 0-based indexing included a simple yet elegant defense of 0-based half-closed interval notation, citing empirical evidence that its use leads to fewer programming errors than any alternative notation.
As persuasive as this list is, one might claim that all of these points (perhaps with the exception of Dijkstra's data-supported claims) still fall within the realm of opinion. But where the GFF-style notation really falls apart is in the encoding of zero-length features. GFF3 simply has no unambiguous notation for specifying insertion sites, cleavage sites, or any other feature that resides between nucleotides. To be clear, the GFF3 specification explicitly addresses this case.
For zero-length features, such as insertion sites, start equals end and the implied site is to the right of the indicated base in the direction of the landmark.
But how is one to distinguish zero-length features from one-length features, which must also be encoded as
start = end?
There is no way to differentiate these two cases without additional (and probably non-canonical) contextual hints, which, as experience shows, come in about as many flavors as there are bioinformaticians.
So although I still personally prefer GFF3 to the competitors, I now acknowledge the use of 1-based closed intervals as one of its biggest weaknesses. That leaves me with a couple of options.
- I could bite the bullet and start using the BED format, despite its shortcomings.
- I could push to change GFF3 to use a demonstrably superior interval notation.
- I could continue using GFF3, despite its shortcomings.
My hesitation with the first option is that BED is so loosely defined that it barely passes for a "standard" format. Of course, people adopt different conventions with all of these formats, some of which are clearly incorrect, and many of which are valid but simply different alternative representations of the same data. But BED gives so much leeway (user's choice of whitespace or tabs for separating fields, optional fields, and sanctioned derivative formats such as "BED detail") that rigorous checks of data integrity can become quite tedious. Not that the majority of bioinformatics programmers actually do rigorous error checking, but you know...
As much as I would welcome an update to the GFF3 spec, I'm afraid interval notation is too central a feature to change with an incremental update. It would likely require a new major release of the specification, and with so much code depending on GFF3, I'm not sure the world is quite ready for GFF4.
So I think for now, my best option is to just stick with GFF3, although I might consider using BED-style notation to represent intervals internally in my software. If I understand correctly, many of the GMOD tools (which are responsible in large part for the success of GFF3) do this, so it's not an unreasonable approach.