block aligner

SIMD-accelerated library for computing global and X-drop affine gap penalty sequence-to-sequence or sequence-to-profile alignments using an adaptive block-based algorithm.

Preprint paper available here.

Example

use block_aligner::scan_block::*;
use block_aligner::scores::*;
use block_aligner::cigar::*;

let block_size = 16;
let gaps = Gaps { open: -2, extend: -1 };
let r = PaddedBytes::from_bytes::<NucMatrix>(b"TTAAAAAAATTTTTTTTTTTT", block_size);
let q = PaddedBytes::from_bytes::<NucMatrix>(b"TTTTTTTTAAAAAAATTTTTTTTT", block_size);

// Align with traceback, but no x drop threshold.
let mut a = Block::<true, false>::new(q.len(), r.len(), block_size);
a.align(&q, &r, &NW1, gaps, block_size..=block_size, 0);
let res = a.res();

assert_eq!(res, AlignResult { score: 7, query_idx: 24, reference_idx: 21 });

let mut cigar = Cigar::new(res.query_idx, res.reference_idx);
a.trace().cigar(res.query_idx, res.reference_idx, &mut cigar);

assert_eq!(cigar.to_string(), "2M6I16M3D");

Algorithm

Pairwise alignment (weighted edit distance) involves computing the scores for each cell of a 2D dynamic programming matrix to find out how two strings can optimally align. However, often it is possible to obtain accurate alignment scores without computing the entire DP matrix, through banding or other means.

Block aligner provides a new efficient way to compute alignments on proteins, DNA sequences, and byte strings. Scores are calculated in a small square block that is shifted down or right in a greedy manner, based on the scores at the edges of the block. This dynamic approach results in a much smaller calculated block area, at the expense of some accuracy. To address problems with handling large gaps, we detect gaps by keeping track of the number of iterations without seeing score increases. We call this "Y-drop", where Y is the threshold number of iterations. When the Y-drop condition is met, the block goes "back in time" to the previous best checkpoint, and the size of the block dynamically increases to attempt to span the large gap.

Block aligner is built to exploit SIMD parallelism on modern CPUs. Currently, AVX2 (256-bit vectors) and WASM SIMD (128-bit vectors) are supported. For score calculations, 16-bit score values (lanes) and 32-bit per block offsets are used.

Install

This library can be used on both stable and nightly Rust channels. The nightly channel is needed for running tests and benchmarks. Additionally, the tests and benchmarks need to run on Linux or MacOS.

To use this as a crate in your Rust project, add the following to your Cargo.toml:

[dependencies]
block-aligner = { version = "^0.2.0", features = ["simd_avx2"] }

Use the simd_wasm feature flag for WASM SIMD support. It is your responsibility to ensure the correct feature to be enabled and supported by the platform that runs the code because this library does not automatically detect the supported SIMD instruction set.

For developing, testing, or using the C API, you should clone this repo and use Rust nightly. In general, when building, you need to specify the correct feature flags through the command line.

For x86 AVX2:

cargo build --features simd_avx2 --release

For WASM SIMD:

cargo build --target=wasm32-wasi --features simd_wasm --release

Most of the instructions below are for benchmarking and testing block aligner.

Data

Some Illumina/Nanopore (DNA) and Uniclust30 (protein) data are used in some tests and benchmarks. You will need to download them by following the instructions in the data readme.

Test

1. scripts/test_avx2.sh or scripts/test_wasm.sh

CI will run these tests when commits are pushed to this repo.

For assessing the accuracy of block aligner on random data, run scripts/accuracy_avx2.sh, scripts/x_drop_accuracy_avx2.sh, or scripts/accuracy_wasm.sh. For Illumina/Nanopore or Uniclust30 data, run scripts/nanopore_accuracy.sh or scripts/uc_accuracy.sh.

For debugging, there exists a debug feature flag that prints out a lot of useful info about the internal state of the aligner while it runs. There is another feature flag, debug_size, that prints the sizes of blocks after they grow. To manually inspect alignments, run scripts/debug_avx2.sh with two sequences as arguments.

Docs

1. scripts/doc_avx2.sh or scripts/doc_wasm.sh

This will build the docs locally.

Compare

Edits were made to Hajime Suzuki's adaptive banding benchmark code and difference recurrence benchmark code. These edits are available here and here, respectively. Go to those repos, then follow the instructions for installing and running the code.

If you run the scripts in those repos for comparing scores produced by different algorithms, you should get .tsv generated files. Then, in this repo's directory, run

scripts/compare_avx2.sh /path/to/file.tsv 50

to get the comparisons. The X-drop threshold is specified after the path.

Benchmark

1. scripts/bench_avx2.sh or scripts/bench_wasm.sh

For benchmarking Nanopore or Uniclust30 data, run scripts/nanopore_bench.sh or scripts/uc_bench.sh.

Profiling with MacOS Instruments

Use

brew install cargo-instruments
RUSTFLAGS="-g" cargo instruments --example profile --release --features simd_avx2 --open

Analyzing performance with LLVM-MCA

Use

scripts/build_ir_asm.sh

to generate assembly output and run LLVM-MCA.

Viewing the assembly

Use either scripts/build_ir_asm.sh, objdump -d on a binary (avoids recompiling code in some cases), or a more advanced tool like Ghidra (has a decompiler, too).

WASM SIMD support

WASM SIMD has been stabilizing in Rust recently, so WASM support should be fairly good. To run WASM programs, you will need wasmtime installed and on your $PATH.

C API

There are C bindings for block aligner. More information on how to use them is located in the C readme.

Data analysis and visualizations

Use the Jupyter notebook in the vis/ directory to gather data and plot them. An easier way to run the whole notebook is to run the vis/run_vis.sh script.

Other SIMD instruction sets

• SSE4.1 (Depends on demand)
• AVX-512 (I don't have a machine to test)
• NEON (I don't have a machine to test)

Old ideas and history

See the ideas file.