4,907 research outputs found
MaxSSmap: A GPU program for mapping divergent short reads to genomes with the maximum scoring subsequence
Programs based on hash tables and Burrows-Wheeler are very fast for mapping
short reads to genomes but have low accuracy in the presence of mismatches and
gaps. Such reads can be aligned accurately with the Smith-Waterman algorithm
but it can take hours and days to map millions of reads even for bacteria
genomes. We introduce a GPU program called MaxSSmap with the aim of achieving
comparable accuracy to Smith-Waterman but with faster runtimes. Similar to most
programs MaxSSmap identifies a local region of the genome followed by exact
alignment. Instead of using hash tables or Burrows-Wheeler in the first part,
MaxSSmap calculates maximum scoring subsequence score between the read and
disjoint fragments of the genome in parallel on a GPU and selects the highest
scoring fragment for exact alignment. We evaluate MaxSSmap's accuracy and
runtime when mapping simulated Illumina E.coli and human chromosome one reads
of different lengths and 10\% to 30\% mismatches with gaps to the E.coli genome
and human chromosome one. We also demonstrate applications on real data by
mapping ancient horse DNA reads to modern genomes and unmapped paired reads
from NA12878 in 1000 genomes. We show that MaxSSmap attains comparable high
accuracy and low error to fast Smith-Waterman programs yet has much lower
runtimes. We show that MaxSSmap can map reads rejected by BWA and NextGenMap
with high accuracy and low error much faster than if Smith-Waterman were used.
On short read lengths of 36 and 51 both MaxSSmap and Smith-Waterman have lower
accuracy compared to at higher lengths. On real data MaxSSmap produces many
alignments with high score and mapping quality that are not given by NextGenMap
and BWA. The MaxSSmap source code is freely available from
http://www.cs.njit.edu/usman/MaxSSmap
Parallel Smith-Waterman Algorithm for Gene Sequencing
Smith-Waterman Algorithm represents a highly robust and efficient parallel computing system development for biological gene sequence. The research work here gives a deep understanding and knowledge transfer about exiting approach for gene sequencing and alignment using Smith-waterman their strength and weaknesses. Smith-Waterman algorithm calculates the local alignment of two given sequences used to identify similar RNA, DNA and protein segments. To identify the enhanced local alignments of biological gene pairs Smith-Waterman algorithm uses dynamic programming approach. It is proficient in finding the optimal local alignment considering the given scoring system.
DOI: 10.17762/ijritcc2321-8169.150515
Revisiting the Speed-versus-Sensitivity Tradeoff in Pairwise Sequence Search
The Smith-Waterman algorithm is a dynamic programming method for determining optimal local alignments between nucleotide or protein sequences. However, it suffers from quadratic time and space complexity. As a result, many algorithmic and architectural enhancements have been proposed to solve this problem, but at the cost of reduced sensitivity in the algorithms or significant expense in hardware, respectively. Hence, there exists a need to evaluate the tradeoffs between the different solutions. This motivation, coupled with the lack of an evaluation metric to quantify these tradeoffs leads us to formally define and quantify the sensitivity of homology search methods so that tradeoffs between sequence-search solutions can be evaluated in a quantitative manner. As an example, though the BLAST algorithm executes significantly faster than Smith-Waterman, we find that BLAST misses 80% of the significant sequence alignments. This paper then presents a highly efficient parallelization of the Smith-Waterman algorithm on the Cell Broadband Engine, a novel hybrid multicore architecture that drives the PlayStation 3 (PS3) game consoles, and emulates BLAST by repeatedly executing the parallelized Smith-Waterman algorithm to search for a query in a given sequence database. Through an innovative mapping of the optimal Smith-Waterman algorithm onto a cluster of PlayStation 3 nodes, our implementation delivers a 10-fold speed-up over a high-end multicore architecture and an 88-fold speed-up over a non-accelerated PS3. Finally, we compare the performance of our implementation of the Smith-Waterman algorithm to that of BLAST and the canonical Smith-Waterman implementation, based on a combination of three factors — execution time (speed), sensitivity, and the actual cost of de-ploying each solution. In the end, our parallelized Smith-Waterman algorithm approaches the speed of BLAST while maintaining ideal sensitivity and achieving low cost through the use of PlayStation 3 game consoles
OSWALD: OpenCL Smith–Waterman on Altera’s FPGA for Large Protein Databases
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. Unfortunately, the Smith–Waterman algorithm has quadratic time complexity, which makes it computationally demanding for large protein databases. In this paper, we present OSWALD, a portable, fully functional and general implementation to accelerate Smith–Waterman database searches in heterogeneous platforms based on Altera’s FPGA. OSWALD exploits OpenMP multithreading and SIMD computing through SSE and AVX2 extensions on the host while taking advantage of pipeline and vectorial parallelism by way of OpenCL on the FPGAs. Performance evaluations on two different heterogeneous architectures with real amino acid datasets show that OSWALD is competitive in comparison with other top-performing Smith–Waterman implementations, attaining up to 442 GCUPS peak with the best GCUPS/watts ratio.First published June 30, 2016. Article available in: Vol. 32, Issue 3, 2018.Facultad de Informátic
Computer Based Test Using the Fisher-Yates Shuffle and Smith Waterman Algorithm
Tests are used to determine a person’s level of understanding of a subject. The inhibiting factors in tests are less varied questions, questions with insufficient difficulty, subjective assessments, and the length of time in their correction. This research aimed to develop a Computer Based Test (CBT) application. The type of questions in this CBT are multiple choice and essays. This CBT employs categorization of questions, randomization of the questions, and automatic assessment. Questions were categorized manually based on Bloom’s Taxonomy of a lecture. Then the randomization process was carried out using the Fisher-Yates Shuffle algorithm for each question category. The Smith Waterman algorithm was used to automatically assess the essay-type questions. The steps of the Smith Waterman algorithm were preprocessing, data comparison using Smith Waterman, and percentage similarities conversion to test scores. The results of the study showed that the CBT application was able to randomize questions using the Fisher-Yates Shuffle algorithm and automatically assess answers using the Smith Waterman algorithm. RMSE was used to measure of the accuracy of the Smith Waterman algorithm: a value of 1.86 was obtained.
Keywords: Computer based test, assessment, Fisher-Yates Shuffle, Smith Waterma
SSW Library: An SIMD Smith-Waterman C/C++ Library for Use in Genomic Applications
Summary: The Smith Waterman (SW) algorithm, which produces the optimal
pairwise alignment between two sequences, is frequently used as a key component
of fast heuristic read mapping and variation detection tools, but current
implementations are either designed as monolithic protein database searching
tools or are embedded into other tools. To facilitate easy integration of the
fast Single Instruction Multiple Data (SIMD) SW algorithm into third party
software, we wrote a C/C++ library, which extends Farrars Striped SW (SSW) to
return alignment information in addition to the optimal SW score. Availability:
SSW is available both as a C/C++ software library, as well as a stand alone
alignment tool wrapping the librarys functionality at
https://github.com/mengyao/Complete- Striped-Smith-Waterman-Library Contact:
[email protected]: 3 pages, 2 figure
OSWALD: OpenCL Smith–Waterman on Altera’s FPGA for Large Protein Databases
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. Unfortunately, the Smith–Waterman algorithm has quadratic time complexity, which makes it computationally demanding for large protein databases. In this paper, we present OSWALD, a portable, fully functional and general implementation to accelerate Smith–Waterman database searches in heterogeneous platforms based on Altera’s FPGA. OSWALD exploits OpenMP multithreading and SIMD computing through SSE and AVX2 extensions on the host while taking advantage of pipeline and vectorial parallelism by way of OpenCL on the FPGAs. Performance evaluations on two different heterogeneous architectures with real amino acid datasets show that OSWALD is competitive in comparison with other top-performing Smith–Waterman implementations, attaining up to 442 GCUPS peak with the best GCUPS/watts ratio.First published June 30, 2016. Article available in: Vol. 32, Issue 3, 2018.Facultad de Informátic
State-of-the-art in Smith-Waterman Protein Database Search on HPC Platforms
Searching biological sequence database is a common and repeated task in bioinformatics and molecular biology. The Smith–Waterman algorithm is the most accurate method for this kind of search. Unfortunately, this algorithm is computationally demanding and the situation gets worse due to the exponential growth of biological data in the last years. For that reason, the scientific community has made great efforts to accelerate Smith–Waterman biological database searches in a wide variety of hardware platforms. We give a survey of the state-of-the-art in Smith–Waterman protein database search, focusing on four hardware architectures: central processing units, graphics processing units, field programmable gate arrays and Xeon Phi coprocessors. After briefly describing each hardware platform, we analyse temporal evolution, contributions, limitations and experimental work and the results of each implementation. Additionally, as energy efficiency is becoming more important every day, we also survey performance/power consumption works. Finally, we give our view on the future of Smith–Waterman protein searches considering next generations of hardware architectures and its upcoming technologies.Instituto de Investigación en InformáticaUniversidad Complutense de Madri
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