High-throughput sequence alignment using Graphics Processing Units

<p>Abstract</p> <p>Background</p> <p>The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and <it>de novo </it>genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies.</p> <p>Results</p> <p>This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs) in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA) from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies.</p> <p>Conclusion</p> <p>MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.</p

1H nuclear magnetic resonance spectroscopy characterisation of metabolic phenotypes in the medulloblastoma of the SMO transgenic mice

BACKGROUND: Human medulloblastomas exhibit diverse molecular pathology. Aberrant hedgehog signalling is found in 20-30% of human medulloblastomas with largely unknown metabolic consequences. METHODS: Transgenic mice over-expressing smoothened (SMO) receptor in granule cell precursors with high incidence of exophytic medulloblastomas were sequentially followed up by magnetic resonance imaging (MRI) and characterised for metabolite phenotypes by ¹H MR spectroscopy (MRS) in vivo and ex vivo using high-resolution magic angle spinning (HR-MAS) ¹H MRS. RESULTS: Medulloblastomas in the SMO mice presented as T₂ hyperintense tumours in MRI. These tumours showed low concentrations of N-acetyl aspartate and high concentrations of choline-containing metabolites (CCMs), glycine, and taurine relative to the cerebellar parenchyma in the wild-type (WT) C57BL/6 mice. In contrast, ¹H MRS metabolite concentrations in normal appearing cerebellum of the SMO mice were not different from those in the WT mice. Macromolecule and lipid ¹H MRS signals in SMO medulloblastomas were not different from those detected in the cerebellum of WT mice. The HR-MAS analysis of SMO medulloblastomas confirmed the in vivo ¹H MRS metabolite profiles, and additionally revealed that phosphocholine was strongly elevated in medulloblastomas accounting for the high in vivo CCM. CONCLUSIONS: These metabolite profiles closely mirror those reported from human medulloblastomas confirming that SMO mice provide a realistic model for investigating metabolic aspects of this disease. Taurine, glycine, and CCM are potential metabolite biomarkers for the SMO medulloblastomas. The MRS data from the medulloblastomas with defined molecular pathology is discussed in the light of metabolite profiles reported from human tumours

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

[EN] Quantitative multinuclear high-resolution magic angle spinning (HRMAS) was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D 1 H and 31P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. 1 H–1 H homonuclear and 1 H–31P heteronuclear correlation experiments enabled the direct assessment of the 1 H–31P spin systems for signals that suffered from overlapping in the 1D 1 H spectra, and linked the information present in the 1D 1 H and 31P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the 31P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from 31P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH3)3 signals of phosphocholine and choline in 1 H spectra of the tissue in these tumour samples.The authors acknowledge the SCSIE-University of Valencia Microscopy Service for the histological preparations. They also acknowledge Martial Piotto (Bruker BioSpin, France) for providing the ERETIC synthetic signal. Furthermore, they acknowledge financial support from the Spanish Government project SAF2007-6547, the Generalitat Valenciana project GVACOMP2009-303, and the E.U.'s VI Framework Programme via the project "Web accessible MR decision support system for brain tumor diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data" (FP6-2002-LSH 503094). CIBER-BBN is an initiative funded by the VI National R&D&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions, and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Esteve Moya, V.; Celda, B.; Martínez Bisbal, MC. (2012). Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies. 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GPU-Based FFT Computation for Multi-Gigabit WirelessHD Baseband Processing

The next generation Graphics Processing Units (GPUs) are being considered for non-graphics applications. Millimeter wave (60&#x2009;Ghz) wireless networks that are capable of multi-gigabit per second (Gbps) transfer rates require a significant baseband throughput. In this work, we consider the baseband of WirelessHD, a 60&#x2009;GHz communications system, which can provide a data rate of up to 3.8&#x2009;Gbps over a short range wireless link. Thus, we explore the feasibility of achieving gigabit baseband throughput using the GPUs. One of the most computationally intensive functions commonly used in baseband communications, the Fast Fourier Transform (FFT) algorithm, is implemented on an NVIDIA GPU using their general-purpose computing platform called the Compute Unified Device Architecture (CUDA). The paper, first, investigates the implementation of an FFT algorithm using the GPU hardware and exploiting the computational capability available. It then outlines the limitations discovered and the methods used to overcome these challenges. Finally a new algorithm to compute FFT is proposed, which reduces interprocessor communication. It is further optimized by improving memory access, enabling the processing rate to exceed 4&#x2009;Gbps, achieving a processing time of a 512-point FFT in less than 200&#x2009;ns using a two-GPU solution