Search results for "Short read"
showing 5 items of 5 documents
An FPGA aligner for short read mapping
2012
The rapid growth of short read datasets poses a new challenge to the mapping of short reads to a reference genome in terms of sensitivity and execution speed. In this work, we present a parallel architecture for short read mapping utilizing field programmable gate array (FPGA)-based hardware. The computation intensive semi-global alignment and the hash table lookup operations are mapped onto an FPGA. The proposed Align Core is implemented with a parallel block structure to gain computational efficiency. We present a new parallel block-wise alignment structure to approximate the conventional dynamic programming algorithm. The performance of our FPGA aligner is compared to the GASSST and BWA …
CUSHAW2-GPU: Empowering Faster Gapped Short-Read Alignment Using GPU Computing
2014
We present CUSHAW2-GPU to accelerate the CUSHAW2 algorithm using compute unified device architecture (CUDA)-enabled GPUs. Two critical GPU computing techniques, namely intertask hybrid CPU-GPU parallelism and tile-based Smith-Waterman map backtracking using CUDA, are investigated to facilitate fast alignments. By aligning both simulated and real reads to the human genome, our aligner yields comparable or better performance compared to BWA-SW, Bowtie2, and GEM. Furthermore, CUSHAW2-GPU with a Tesla K20c GPU achieves significant speedups over the multithreaded CUSHAW2, BWA-SW, Bowtie2, and GEM on the 12 cores of a high-end CPU for both single-end and paired-end alignment.
Accelerating short read mapping on an FPGA (abstract only)
2012
The explosive growth of short read datasets produced by high throughput DNA sequencing technologies poses a challenge to the mapping of short reads to a reference genome in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generally too slow for large-scale applications. Although a number of short read mapping software tools have been proposed, designs based on hardware are relatively rare. In this paper, we present a hybrid system for short read mapping utilizing both software and field programmable gate array (FPGA)-based hardware. The compute intensive semi-g…
Parallel and scalable short-read alignment on multi-core clusters using UPC++
2016
[Abstract]: The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown to obtain high quality mappings at the expense of long execution times. Finding fast yet accurate software solutions is of high importance to research, since availability and size of NGS datasets continue to increase. In this work we present an efficient parallelization approach for NGS short-read alignment on multi-core clusters. Our approach takes advantage of a distributed shared memory programming model based on the new UPC++ language. Experimental results using the …
An Overview of the Application of Deep Learning in Short Read Sequence Classification
2020
AbstractAdvances in sequencing technology have led to an ever increasing amount of available short read sequencing data. This has, consequently, exacerbated the need for efficient and precise classification tools that can be used in the analysis of this data. As it stands, recent years have shown that massive leaps in performance can be achieved when it comes to approaches that are based in heuristics, and alongside these improvements there has been an ever increasing interest in applying deep learning techniques to revolutionize this classification task. We attempt to gather up these approaches and to evaluate their performance in a reproducible fashion to get a better perspective on the c…