ScalableAligner: a fast NGS mapping tool for shared-memory system

Laser-induced surface acoustic wave spectroscopy (LISAWS) allows quick and nondestructive evaluation of the elastic properties such as the Young’s modulus of coatings, surfaces and surface-near bulk materials. Furthermore, the mechanical weakening due to cracks and pores can be evaluated, as they influence the propagation of surface waves as well. This makes the method a fast, accurate and versatile tool for surface characterization, and it is increasingly used in research and development, and quality control. The short measurement time of the LISAWS method allows the time-efficient distribution of the effective Young's modulus over the coated surface to be determined. For this purpose, an industrial LAwave measurement system was automated to allow for processing of a larger number of samples and fast mappings. The investigated coating materials were thermally sprayed Al2O3 insulation coatings and WC-reinforced 316L steel coatings on brake disks produced by laser cladding, respectively. For the Al2O3 coatings, the correlation between the Young's modulus and its areal distribution is shown for different process parameters, such as spray gun movement direction or spray distance, and compared with results from pull-off tests. For the WC/316L-coated brake disks, the distribution of the wave velocity over the coated surfaces or the two coated sides of different disks with varying coating qualities is used to assess the coating quality and homogeneity.

Faults form dense, complex multi‐scale networks generally featuring a master fault and myriads of smaller‐scale faults and fractures off its trace, often referred to as damage. Quantification of the architecture of these complex networks is critical to understanding fault and earthquake mechanics. Commonly, faults are mapped manually in the field or from optical images and topographic data through the recognition of the specific curvilinear traces they form at the ground surface. However, manual mapping is time‐consuming, which limits our capacity to produce complete representations and measurements of the fault networks. To overcome this problem, we have adopted a machine learning approach, namely a U‐Net Convolutional Neural Network (CNN), to automate the identification and mapping of fractures and faults in optical images and topographic data. Intentionally, we trained the CNN with a moderate amount of manually created fracture and fault maps of low resolution and basic quality, extracted from one type of optical images (standard camera photographs of the ground surface). Based on a number of performance tests, we select the best performing model, MRef, and demonstrate its capacity to predict fractures and faults accurately in image data of various types and resolutions (ground photographs, drone and satellite images and topographic data). MRefexhibits good generalization capacities, making it a viable tool for fast and accurate mapping of fracture and fault networks in image and topographic data. The MRefmodel can thus be used to analyze fault organization, geometry, and statistics at various scales, key information to understand fault and earthquake mechanics.

Recent advancements in long-read sequencing have enabled the telomere-to-telomere (complete) assembly of a human genome and are now contributing to the haplotype-resolved complete assemblies of multiple human genomes. Because the accuracy of read mapping tools deteriorates in highly repetitive regions, there is a need to develop accurate, error-exposing (detecting potential assembly errors), and diploid-aware (distinguishing different haplotypes) tools for read mapping in complete assemblies. We describe the first accurate, error-exposing, and partially diploid-aware VerityMap tool for long-read mapping to complete assemblies.

Electrocorticography (ECoG) is a powerful tool for presurgical functional mapping. Power increase in the high gamma band has been observed from ECoG electrodes on the surface of the sensory motor cortex during the execution of body movements. In this study the authors aim to validate the clinical usage of high gamma activity in presurgical mapping by comparing ECoG mapping with traditional direct electrical cortical stimulation (ECS) and functional MRI (fMRI) mapping. Seventeen patients with epilepsy participated in an ECoG motor mapping experiment. The patients executed a 5-minute hand/tongue movement task while the ECoG signal was recorded. All 17 patients also underwent extraoperative ECS mapping to localize the motor cortex. Eight patients also participated in a presurgical fMRI study. The high gamma activity on ECoG was modeled using the general linear model (GLM), and the regions showing significant gamma power increase during the task condition compared with the rest condition were localized. The maps derived from GLM-based ECoG mapping, ECS, and fMRI were then compared. High gamma activity in the motor cortex can be reliably modulated by motor tasks. Localization of the motor regions achieved with GLM-based ECoG mapping was consistent with the localization determined by ECS. The maps also appeared to be highly localized compared with the fMRI activations. Using the ECS findings as the reference, GLM-based ECoG mapping showed a significantly higher sensitivity than fMRI (66.7% for ECoG, 52.6% for fMRI, p<0.05), while the specificity was high for both techniques (>97%). If the current-spreading effect in ECS is accounted for, ECoG mapping may produce maps almost identical to those produced by ECS mapping (100% sensitivity and 99.5% specificity). General linear model-based ECoG mapping showed a superior performance compared to traditional ECS and fMRI mapping in terms of efficiency and accuracy. Using this method, motor functions can be reliably mapped in less than 5 minutes.

ABSTRACT: Mapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in open-pit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLI-derived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas.

Advances in epilepsy studies have shown that specific changes in hemodynamics precede and accompany seizure onset and propagation. However, it has been challenging to noninvasively detect these changes in real time and in humans, due to the lack of fast functional neuroimaging tools. In this study, we present a functional diffuse optical tomography (DOT) method with the guidance of an anatomical human head atlas for 3-dimensionally mapping the brain in real time. Central to our DOT system is a human head interface coupled with a technique that can incorporate topological information of the brain surface into the DOT image reconstruction. The performance of the DOT system was tested by imaging motor tasks-involved brain activities on N = 6 subjects (3 epilepsy patients and 3 healthy controls). We observed diffuse areas of activations from the reconstructed [HbT] images of patients, relative to more focal activations for healthy subjects. Moreover, significant pretask hemodynamic activations were also seen in the motor cortex of patients, which indicated abnormal activities persistent in the brain of an epilepsy patient. This work demonstrates that fast functional DOT is a valuable tool for noninvasive 3-dimensional mapping of brain hemodynamics.

The OneMap™ tool, a new software feature of the EnSite Velocity™ System, and the new Inquiry™ AFocus™ II double loop duodecapolar diagnostic catheter (DDC) were created to provide faster data collection to efficiently deal with complex arrhythmias such as persistent atrial fibrillation ablation (AF). Our study was performed to compare acquisition criteria, time needed to create the maps, number of collected points, relevance of complex fractionated atrial electrogram (CFE) mapping and correlation between CFE maps with the new DDC and a 4mm irrigated ablation catheter (ABL), Therapy™ Cool Path™ Duo, using the OneMap tool. Ten patients undergoing persistent AF ablation were enrolled. With the DDC, more points were collected (485±173 versus 183±37) and the time needed to create CFE maps was shorter (12±4 versus 24±2 minutes). There were 39 zones detected with the DDC against 35 with the ABL. The correlation between the maps was 80%; however, four additional regions were detected with the DDC (an 11% increase). In conclusion, the Inquiry AFocus II DDC is a feasible, fast and accurate tool for automatic CFE mapping using OneMap.

BackgroundVarious indexing techniques have been applied by next generation sequencing read mapping tools. The choice of a particular data structure is a trade-off between memory consumption, mapping throughput, and construction time.ResultsWe present the succinct hash index – a novel data structure for read mapping which is a variant of the classical q-gram index with a particularly small memory footprint occupying between 3.5 and 5.3 GB for a human reference genome for typical parameter settings. The succinct hash index features two novel seed selection algorithms (group seeding and variable-length seeding) and an efficient parallel construction algorithm, which we have implemented to design the FEM (Fast(F) and Efficient(E) read Mapper(M)) mapper. FEM can return all read mappings within a given edit distance. Our experimental results show that FEM is scalable and outperforms other state-of-the-art all-mappers in terms of both speed and memory footprint. Compared to Masai, FEM is an order-of-magnitude faster using a single thread and two orders-of-magnitude faster when using multiple threads. Furthermore, we observe an up to 2.8-fold speedup compared to BitMapper and an order-of-magnitude speedup compared to BitMapper2 and Hobbes3.ConclusionsThe presented succinct index is the first feasible implementation of the q-gram index functionality that occupies around 3.5 GB of memory for a whole human reference genome. FEM is freely available at https://github.com/haowenz/FEM.