- 项目是基于自适应比对带的偏序比对启发式加速方法（abpoa）的CUDA C实现，目的是利用GPU并行计算提高计算的并行度。
- 原abpoa是我实验室师兄设计实现的，实现采用SIMD并行计算，其github地址为：https://github.com/yangao07/abPOA
- 我的工作集中在src/simd_abpoa_align.cu、src/cuda_abpoa_align.h的实现，以及对makefile的CUDA C相关改造。
- 我对原abpoa的偏序比对计算部分进行CUDA C实现，实现了convex比对模式下的全局比对，极大提高了计算的并行度。
- 同时我熟悉整个项目的计算流程、相关数据结构。
git clone https://github.com/1170300727/cudaPOA
cd cudaPOA
Make from source and run with test data:
make; ./bin/abpoa ./test_data/seq.fa > cons.fa
Or, install via conda and run with test data:
conda install -c bioconda abpoa
abpoa ./test_data/seq.fa > cons.fa
abPOA is an extended version of Partial Order Alignment (POA) that performs adaptive banded dynamic programming (DP) with an SIMD implementation. abPOA can perform multiple sequence alignment (MSA) on a set of input sequences and generate a consensus sequence by applying the heaviest bundling algorithm to the final alignment graph.
abPOA can generate high-quality consensus sequences from error-prone long reads and offer significant speed improvement over existing tools.
abPOA supports three alignment modes (global, local, extension) and flexible scoring schemes that allow linear, affine and convex gap penalties. It right now supports SSE2/SSE4.1/AVX2/AVX512F/AVX512BW vectorization and more advanced instructions will be supported in the future.
For more information, please refer to our preprint paper.
On Linux/Unix and Mac OS, abPOA can be installed via
conda install -c bioconda abpoa # install abPOA program
You can also build abPOA from source files. Make sure you have gcc (>=6.4.0) and zlib installed before compiling. It is recommended to download the latest release.
wget https://github.com/yangao07/abPOA/releases/download/v1.0.3/abPOA-v1.0.3.tar.gz
tar -zxvf abPOA-v1.0.3.tar.gz
cd abPOA-v1.0.3; make
Or, you can use git clone command to download the source code.
This gives you the latest version of abPOA, which might be still under development.
git clone https://github.com/yangao07/abPOA.git
cd abPOA; make
If you meet any compiling issue, please try the pre-built binary file:
wget https://github.com/yangao07/abPOA/releases/download/v1.0.3/abPOA-v1.0.3_x64-linux.tar.gz
tar -zxvf abPOA-v1.0.3_x64-linux.tar.gz
abpoa seq.fa > cons.fa
abpoa seq.fa -r2 > cons.out
abpoa seq.fa -g poa.png > cons.fa
See Plot of alignment graph for more details about the plot file.
Usage: abpoa [options] <in.fa/fq> > cons.fa/msa.out
Options:
Alignment:
-m --aln-mode INT alignment mode [0]
0: global, 1: local, 2: extension
-M --match INT match score [2]
-X --mismatch INT mismatch penalty [4]
-O --gap-open INT(,INT) gap opening penalty (O1,O2) [4,24]
-E --gap-ext INT(,INT) gap extension penalty (E1,E2) [2,1]
abPOA provides three gap penalty modes, cost of a g-long gap:
- convex (default): min{O1+g*E1, O2+g*E2}
- affine (set O2 as 0): O1+g*E1
- linear (set O1 as 0): g*E1
Adaptive banded DP:
-b --extra-b INT first adaptive banding parameter [10]
set b as < 0 to disable adaptive banded DP
-f --extra-f FLOAT second adaptive banding parameter [0.01]
the number of extra bases added on both sites of the band is
b+f*L, where L is the length of the aligned sequence
Input/Output:
-l --in-list input file is a list of sequence file names [False]
each line is one sequence file containing a set of sequences
which will be aligned by abPOA to generate a consensus sequence
-o --output FILE ouput to FILE [stdout]
-r --result INT output result mode [0]
- 0: consensus (FASTA format)
- 1: MSA (PIR format)
- 2: both 0 & 1
-g --out-pog FILE dump final alignment graph to FILE (.pdf/.png) [Null]
-h --help print this help usage information
-v --version show version number
abPOA works with FASTA, FASTQ, gzip'd FASTA(.fa.gz) and gzip'd FASTQ(.fq.gz) formats. The input file is expected to contains multiple sequences which will be processed sequentially to perform the iterative sequence-to-graph (partial order) alignment.
abPOA can also take a list of file names as input with option -l, where each line is the path to one
file containing multiple sequences. Each sequence file is then individually aligned by abPOA to generate a
consensus sequence.
By default, abPOA only outputs the consensus sequence generated from the final alignment agraph. It is in FASTA format with the name field set as "Consensus_sequence". For example:
>Consensus_sequence
ACGTGTACACGTTGAC
abPOA cano also output the row-column multiple sequence alignment (RC-MSA) of all the aligned sequences in PIR format
with an additional FASTA header >Multiple_sequence_alignment. For example:
>Multiple_sequence_alignment
ACGTGTACA-GTTGAC
A-G-GTACACGTT-AC
A-GTGT-CACGTTGAC
ACGTGTACA--TTGAC
The - in the sequence stands for alignment gap.
abPOA can generate a plot of the final partial order alignment graph with the help of graphviz dot.
For example:
The numbers inside the nodes are the node IDs. The numbers on the edges are the edge weights.
S and E are the auxiliary start and end nodes that have no sequence bases.
Make sure you have dot installed beforing using abPOA to generate the plot.
For Linux/Unix systems: sudo apt-get install graphviz.
abPOA is not only a stand-alone tool for MSA and consensus calling, it can also work as a programming library. example.c shows how to use the C APIs of abPOA to take a set of sequences as input and perform MSA and consensus calling. Basically, the library file libabpoa.a and two header files abpoa.h and simd_instruction.h are needed to make the abPOA library work in your program.
abPOA also provides Python bindings to all the primary C APIs. Refer to python/README.md for more details.
Yan Gao [email protected]
Yi Xing [email protected]
Yadong Wang [email protected]
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