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C++ library for genomic region based storage and querying

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Mappable

Mappable is a powerful C++ template library for genomic region storage, manipulation, and querying. Mappable is independent of the data structure used to store the underlying objects, instead relying on C++'s curiously recurring template pattern (CRTP) to define region concepts and ordering. This allows Mappable to build on standard C++ containers and algorithms to give an efficient, flexible, and expressive set of region based containers and algorithms which act directly on Mappable objects. Mappable was originally developed as part of the variant caller octopus, where it is used extensively. It has been heavily tested and benchmarked, and can perform orders of magnitude faster than other approaches (see benchmark.cpp).

Requirements

  • A C++14 compiler and standard library implementation
  • Boost 1.58 or greater

To compile the example you will also need CMake 3.5 or greater:

$ mkdir build && cd build
$ cmake .. && make
$ ./example

Basic usage

The starting point for any Mappable type is to inherit from Mappable and implement the mapped_region member method:

struct MyMappableType : public Mappable<MyMappableType>
{
    ContigRegion region;
    MyDataType data;
    const auto& mapped_region() const noexcept { return region; }; // required by Mappable
    // Constructors and other member methods
};

Now MyMappableType can be used with all of Mappable's algorithms:

std::vector<MyMappableType> mappables {};
mappables.emplace_back(ContigRegion {0, 1}, "A");
mappables.emplace_back(ContigRegion {1, 3}, "B");
mappables.emplace_back(ContigRegion {2, 4}, "C");
auto overlapped = overlap_range(mappables, ContigRegion {1, 3}); // iterator range
std::cout << overlapped << std::endl;
std::cout << count_contained(mappables, ContigRegion {1, 3}) << std::endl; // 1

The library also includes some helpful containers that are heavily optimised for Mappable types:

MyMappableType a {ContigRegion {0, 1}, "A"}, b {ContigRegion {1, 3}, "B"};
MappableFlatSet<MyMappableType> mappables {a};
mappables.insert(b);
mappables.emplace(ContigRegion {1, 3}, "C");
mappables.erase(b);

How it works

Fundamental to a Mappable object is the mapped_region() public method which enables compile time static polymorphism using the CRTP. As the base Mappable template class is empty, there is no memory overhead to deriving from Mappable. The mapped_region() method must return one of the two fundamental region types, ContigRegion or GenomicRegion. ContigRegion simply defines a range, whilst GenomicRegion defines a contig plus ContigRegion. Both ContigRegion and GenomicRegion have a comprehensive free function interface which can be invoked by any Mappable object via a callback to mapped_region(). For example, both ContigRegion and GenomicRegion implement the overlaps(const M&lhs, const M& rhs) method which returns whether or not lhs and rhs are overlapping. In Mappables interface, there is also an overlaps method that accepts any two Mappable types that forwards the call to the correct overlaps implementation. The first benefit of this approach is it allows users to call overlaps using overlaps(lhs, rhs) rather than overlaps(lhs.mapped_region(), rhs.mapped_region()). However, more importantly, it allows one to write general algorithms that are independent of the Mappable objects they operate on.

The Mappable algorithms library is designed in a similar way to the C++ STL; most algorithms operate on collections of Mappable objects via iterator ranges. Usually the range must be sorted with respect to operator< for the underlying Mappable region type (ContigRegion or GenomicRegion). How the Mappable objects are actually stored in memory is only important so far as it determines the iterator type that each algorithm can operate on. This allows users to choose a data structure that has the best time and memory complexity requirements for their particular use case.

Although mappable algorithms can be used directly with standard conforming containers, the Mappable library includes some of it's own containers. The reason for this is that some mappable algorithms (predominantly overlap_range) have faster implementations if the range of Mappable objects satisfies a stronger ordering than that defined by operator<. In particular, operator<implies an ordering from 'left to right', but does not, and in the general case cannot, require a 'right to left' ordering. However, some collections will naturally satisfy the 'right to left' ordering in addition to the 'left to right' one required by operator<. If this is the case,overlap_range has worst-case complexity logarithmic (apposed to amortized worse case logarithmic). There is also a faster implementation of overlap_range if the maximum sizedMappable object is known. The provided containers simply keep track of these properties, and call the most appropriate mappable algorithm.

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