ArticleGenes2019
PipeMEM: A Framework to Speed Up BWA-MEM in Spark with Low Overhead.
Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Development of InDel-Based Identification Methods for Wild and Domesticated Populations: A Case Study ofAnimals : an open access journal from MDPI · 2026Article
- Whole genome sequencing and resequencing provide insight into the genetic structure of wild Ophiocordyceps sinensis.BMC genomics · 2025Article
- Bioinformatics characterization of variants of uncertain significance in pediatric sensorineural hearing loss.Frontiers in pediatrics · 2024Article
- CircRNA expression profiling of PBMCs from patients with hepatocellular carcinoma by RNA-sequencing.Experimental and therapeutic medicine · 2021Article
- Article
- Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry.International journal of molecular sciences · 2021Review
- Multi-Omics Characterization of Circular RNA-Encoded Novel Proteins Associated With Bladder Outlet Obstruction.Frontiers in cell and developmental biology · 2021Article
- Big Data in metagenomics: Apache Spark vs MPI.PloS one · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
(1) Background: DNA sequence alignment process is an essential step in genome analysis. BWA-MEM has been a prevalent single-node tool in genome alignment because of its high speed and accuracy. The exponentially generated genome data requiring a multi-node solution to handle large volumes of data currently remains a challenge. Spark is a ubiquitous big data platform that has been exploited to assist genome alignment in handling this challenge. Nonetheless, existing works that utilize Spark to optimize BWA-MEM suffer from higher overhead. (2) Methods: In this paper, we presented PipeMEM, a framework to accelerate BWA-MEM with lower overhead with the help of the pipe operation in Spark. We additionally proposed to use a pipeline structure and in-memory-computation to accelerate PipeMEM. (3) Results: Our experiments showed that, on paired-end alignment tasks, our framework had low overhead. In a multi-node environment, our framework, on average, was 2.27× faster compared with BWASpark (an alignment tool in Genome Analysis Toolkit (GATK)), and 2.33× faster compared with SparkBWA. (4) Conclusions: PipeMEM could accelerate BWA-MEM in the Spark environment with high performance and low overhead.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.