High-Performance FPGA-Based BWA-MEM Accelerator

There is no denying that Bioinformatics is one of the most important realms for our forthcoming development. As a demonstration of this fact, a plethora of new algorithms that were published over the last decade. Those significantly boost up the processes of biological analysis, especially for DNA alignment. Despite their undeniable contributions, it is still far more to state that DNA alignment has already achieved the ideal performance. In this work, we focus on the DNA alignment system which is based on our improved BWA-MEM algorithm that we have already published. Besides that, we also propose some optimization methods which was applied in order to improve the performance as well as the stability of our entire system. The system offers a speed-up by 46.52x when compared with the other computing platforms.

Devising Digital Twins DNA Paradigm for Modeling ISO-Based City Services

Digital twins (DTs) technology has recently gained attention within the research community due to its potential to help build sustainable smart cities. However, there is a gap in the literature: currently no unified model for city services has been proposed that can guarantee interoperability across cities, capture each city’s unique characteristics, and act as a base for modeling digital twins. This research aims to fill that gap. In this work, we propose the DT-DNA model in which we design a city services digital twin, with the goal of reflecting the real state of development of a city’s services towards enhancing its citizens’ quality of life (QoL). As it was designed using ISO 37120, one of the leading international standards for city services, the model guarantees interoperability and allows for easy comparison of services within and across cities. In order to test our model, we built DT-DNA sequences of services in both Quebec City and Boston and then used a DNA alignment tool to determine the matching percentage between them. Results show that the DT-DNA sequences of services in both cities are 46.5% identical. Ground truth comparisons show a similar result, which provides a preliminary proof-of-concept for the applicability of the proposed model and framework. These results also imply that one city performs better than the other. Therefore, we propose an algorithm to compare cities based on the proposed DT-DNA and, using Boston and Quebec City as a case study, demonstrate that Boston has better services towards enhancing QoL for its citizens.

A Bayesian Mutation–Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

In recent years, codon substitution models based on the mutation–selection principle have been extended for the purpose of detecting signatures of adaptive evolution in protein-coding genes. However, the approaches used to date have either focused on detecting global signals of adaptive regimes—across the entire gene—or on contexts where experimentally derived, site-specific amino acid fitness profiles are available. Here, we present a Bayesian site-heterogeneous mutation–selection framework for site-specific detection of adaptive substitution regimes given a protein-coding DNA alignment. We offer implementations, briefly present simulation results, and apply the approach on a few real data sets. Our analyses suggest that the new approach shows greater sensitivity than traditional methods. However, more study is required to assess the impact of potential model violations on the method, and gain a greater empirical sense its behavior on a broader range of real data sets. We propose an outline of such a research program.

Bit-Vector-Based Hardware Accelerator for DNA Alignment Tools

Next generation sequencing technologies have noticeably improved in the last decade. Time and cost of whole genome sequencing are important challenges that must be reduced, opening unprecedented opportunities to various research and development areas. The alignment or mapping of small reads produced by sequencing machines to reference genomes of billions of nucleotides is a fundamental task in this sequencing process. It is computationally highly demanding and has become the bottleneck of the DNA analysis process. This paper proposes hardware acceleration based on FPGA of the Myers bit-parallelized algorithm, appropriately modified to be used in the extend stage of DNA alignment tools. The proposed design can be employed in conjunction with software functions, as it constitutes an extremely fast heterogeneous DNA alignment system. The implementation results show a speedup of up to [Formula: see text] relative to a sequential implementation only in software. In addition, due to the limited use of FPGA resources and the modular design, multiple modules can be used to completely populate the chip, further increasing the computing speed.

Machine Boss: rapid prototyping of bioinformatic automata

Motivation Many software libraries for using Hidden Markov Models in bioinformatics focus on inference tasks, such as likelihood calculation, parameter-fitting and alignment. However, construction of the state machines can be a laborious task, automation of which would be time-saving and less error-prone. Results We present Machine Boss, a software tool implementing not just inference and parameter-fitting algorithms, but also a set of operations for manipulating and combining automata. The aim is to make prototyping of bioinformatics HMMs as quick and easy as the construction of regular expressions, with one-line ‘recipes’ for many common applications. We report data from several illustrative examples involving protein-to-DNA alignment, DNA data storage and nanopore sequence analysis. Availability and implementation Machine Boss is released under the BSD-3 open source license and is available from http://machineboss.org/. Supplementary information Supplementary data are available at Bioinformatics online.

SHOGUN: a modular, accurate and scalable framework for microbiome quantification

Summary The software pipeline SHOGUN profiles known taxonomic and gene abundances of short-read shotgun metagenomics sequencing data. The pipeline is scalable, modular and flexible. Data analysis and transformation steps can be run individually or together in an automated workflow. Users can easily create new reference databases and can select one of three DNA alignment tools, ranging from ultra-fast low-RAM k-mer-based database search to fully exhaustive gapped DNA alignment, to best fit their analysis needs and computational resources. The pipeline includes an implementation of a published method for taxonomy assignment disambiguation with empirical Bayesian redistribution. The software is installable via the conda resource management framework, has plugins for the QIIME2 and QIITA packages and produces both taxonomy and gene abundance profile tables with a single command, thus promoting convenient and reproducible metagenomics research. Availability and implementation https://github.com/knights-lab/SHOGUN.

Sequence Analysis of the K13-Propeller Gene in Artemisinin Challenging Plasmodium falciparum Isolates from Malaria Endemic Areas of Odisha, India: A Molecular Surveillance Study

Estimation of the spread and advancement of Plasmodium falciparum artemisinin-resistant parasites can be done by probing polymorphisms in the kelch (Pfk13) domain (a validated molecular marker). This study aimed to provide baseline information for future artemisinin surveillance by analyzing the k13-propeller domain in P. falciparum field isolates collected from 24 study areas in 14 malaria hot spots of Odisha (previously Orissa) during July 2018-January 2019. A total of 178 P. falciparum mono infections were assessed. An 849-base pair fragment encoding the Pfk13 propeller was amplified by nested polymerase chain reaction and sequenced in both directions (PCR). After DNA alignment with the 3D7 reference sequence, all samples were found to be wild type. It can be anticipated that malaria public health is not under direct threat in Odisha relating to ART resistance.