Short-read aligner performance in germline variant identification.

MOTIVATION: Read alignment is an essential first step in the characterization of DNA sequence variation. The accuracy of variant-calling results depends not only on the quality of read alignment and variant-calling software but also on the interaction between these complex software tools. RESULTS: In this review, we evaluate short-read aligner performance with the goal of optimizing germline variant-calling accuracy. We examine the performance of three general-purpose short-read aligners-BWA-MEM, Bowtie 2, and Arioc-in conjunction with three germline variant callers: DeepVariant, FreeBayes, and GATK HaplotypeCaller. We discuss the behavior of the read aligners with regard to the data elements on which the variant callers rely, and illustrate how the runtime configurations of these software tools combine to affect variant-calling performance. AVAILABILITY AND IMPLEMENTATION: The quick brown fox jumps over the lazy dog.

BiocMAP: a Bioconductor-friendly, GPU-accelerated pipeline for bisulfite-sequencing data.

BACKGROUND: Bisulfite sequencing is a powerful tool for profiling genomic methylation, an epigenetic modification critical in the understanding of cancer, psychiatric disorders, and many other conditions. Raw data generated by whole genome bisulfite sequencing (WGBS) requires several computational steps before it is ready for statistical analysis, and particular care is required to process data in a timely and memory-efficient manner. Alignment to a reference genome is one of the most computationally demanding steps in a WGBS workflow, taking several hours or even days with commonly used WGBS-specific alignment software. This naturally motivates the creation of computational workflows that can utilize GPU-based alignment software to greatly speed up the bottleneck step. In addition, WGBS produces raw data that is large and often unwieldy; a lack of memory-efficient representation of data by existing pipelines renders WGBS impractical or impossible to many researchers. RESULTS: We present BiocMAP, a Bioconductor-friendly methylation analysis pipeline consisting of two modules, to address the above concerns. The first module performs computationally-intensive read alignment using Arioc, a GPU-accelerated short-read aligner. Since GPUs are not always available on the same computing environments where traditional CPU-based analyses are convenient, the second module may be run in a GPU-free environment. This module extracts and merges DNA methylation proportions-the fractions of methylated cytosines across all cells in a sample at a given genomic site. Bioconductor-based output objects in R utilize an on-disk data representation to drastically reduce required main memory and make WGBS projects computationally feasible to more researchers. CONCLUSIONS: BiocMAP is implemented using Nextflow and available at http://research.libd.org/BiocMAP/ . To enable reproducible analysis across a variety of typical computing environments, BiocMAP can be containerized with Docker or Singularity, and executed locally or with the SLURM or SGE scheduling engines. By providing Bioconductor objects, BiocMAP's output can be integrated with powerful analytical open source software for analyzing methylation data.

Performance optimization in DNA short-read alignment.

SUMMARY: Over the past decade, short-read sequence alignment has become a mature technology. Optimized algorithms, careful software engineering and high-speed hardware have contributed to greatly increased throughput and accuracy. With these improvements, many opportunities for performance optimization have emerged. In this review, we examine three general-purpose short-read alignment tools-BWA-MEM, Bowtie 2 and Arioc-with a focus on performance optimization. We analyze the performance-related behavior of the algorithms and heuristics each tool implements, with the goal of arriving at practical methods of improving processing speed and accuracy. We indicate where an aligner's default behavior may result in suboptimal performance, explore the effects of computational constraints such as end-to-end mapping and alignment scoring threshold, and discuss sources of imprecision in the computation of alignment scores and mapping quality. With this perspective, we describe an approach to tuning short-read aligner performance to meet specific data-analysis and throughput requirements while avoiding potential inaccuracies in subsequent analysis of alignment results. Finally, we illustrate how this approach avoids easily overlooked pitfalls and leads to verifiable improvements in alignment speed and accuracy. CONTACT: richard.wilton@jhu.edu. SUPPLEMENTARY INFORMATION: Appendices referenced in this article are available at Bioinformatics online.

Molecular phenotypes associated with antipsychotic drugs in the human caudate nucleus.

Antipsychotic drugs are the current first-line of treatment for schizophrenia and other psychotic conditions. However, their molecular effects on the human brain are poorly studied, due to difficulty of tissue access and confounders associated with disease status. Here we examine differences in gene expression and DNA methylation associated with positive antipsychotic drug toxicology status in the human caudate nucleus. We find no genome-wide significant differences in DNA methylation, but abundant differences in gene expression. These gene expression differences are overall quite similar to gene expression differences between schizophrenia cases and controls. Interestingly, gene expression differences based on antipsychotic toxicology are different between brain regions, potentially due to affected cell type differences. We finally assess similarities with effects in a mouse model, which finds some overlapping effects but many differences as well. As a first look at the molecular effects of antipsychotics in the human brain, the lack of epigenetic effects is unexpected, possibly because long term treatment effects may be relatively stable for extended periods.

Arioc: High-concurrency short-read alignment on multiple GPUs.

In large DNA sequence repositories, archival data storage is often coupled with computers that provide 40 or more CPU threads and multiple GPU (general-purpose graphics processing unit) devices. This presents an opportunity for DNA sequence alignment software to exploit high-concurrency hardware to generate short-read alignments at high speed. Arioc, a GPU-accelerated short-read aligner, can compute WGS (whole-genome sequencing) alignments ten times faster than comparable CPU-only alignment software. When two or more GPUs are available, Arioc's speed increases proportionately because the software executes concurrently on each available GPU device. We have adapted Arioc to recent multi-GPU hardware architectures that support high-bandwidth peer-to-peer memory accesses among multiple GPUs. By modifying Arioc's implementation to exploit this GPU memory architecture we obtained a further 1.8x-2.9x increase in overall alignment speeds. With this additional acceleration, Arioc computes two million short-read alignments per second in a four-GPU system; it can align the reads from a human WGS sequencer run-over 500 million 150nt paired-end reads-in less than 15 minutes. As WGS data accumulates exponentially and high-concurrency computational resources become widespread, Arioc addresses a growing need for timely computation in the short-read data analysis toolchain.

The Terabase Search Engine: a large-scale relational database of short-read sequences.

MOTIVATION: DNA sequencing archives have grown to enormous scales in recent years, and thousands of human genomes have already been sequenced. The size of these data sets has made searching the raw read data infeasible without high-performance data-query technology. Additionally, it is challenging to search a repository of short-read data using relational logic and to apply that logic across samples from multiple whole-genome sequencing samples. RESULTS: We have built a compact, efficiently-indexed database that contains the raw read data for over 250 human genomes, encompassing trillions of bases of DNA, and that allows users to search these data in real-time. The Terabase Search Engine enables retrieval from this database of all the reads for any genomic location in a matter of seconds. Users can search using a range of positions or a specific sequence that is aligned to the genome on the fly. AVAILABILITY AND IMPLEMENTATION: Public access to the Terabase Search Engine database is available at http://tse.idies.jhu.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Arioc: GPU-accelerated alignment of short bisulfite-treated reads.

Motivation: The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a large genome involves a significant computational burden beyond that required to align non-bisulfite-treated reads. In the analysis of BS-seq data, this can present an important performance bottleneck that can be mitigated by appropriate algorithmic and software-engineering improvements. One strategy is to modify the read-alignment algorithms by integrating the logic related to BS-seq alignment, with the goal of making the software implementation amenable to optimizations that lead to higher speed and greater sensitivity than might otherwise be attainable. Results: We evaluated this strategy using Arioc, a short-read aligner that uses GPU (general-purpose graphics processing unit) hardware to accelerate computationally-expensive programming logic. We integrated the BS-seq computational logic into both GPU and CPU code throughout the Arioc implementation. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments reported by well-known CPU-based BS-seq read aligners. With simulated reads, Arioc's accuracy is equal to or better than the other read aligners we evaluated. With human sequencing reads, Arioc's throughput is at least 10 times faster than existing BS-seq aligners across a wide range of sensitivity settings. Availability and implementation: The Arioc software is available for download at https://github.com/RWilton/Arioc. It is released under a BSD open-source license. Supplementary information: Supplementary data are available at Bioinformatics online.

Plasma CVD of hydrogenated boron-carbon thin films from triethylboron.

Low-temperature chemical vapor deposition (CVD) of B-C thin films is of importance for neutron voltaics and semiconductor technology. The highly reactive trialkylboranes, with alkyl groups of 1-4 carbon atoms, are a class of precursors that have been less explored for low-temperature CVD of B-C films. Herein, we demonstrate plasma CVD of B-C thin films using triethylboron (TEB) as a single source precursor in an Ar plasma. We show that the film density and B/C ratio increases with increasing plasma power, reaching a density of 2.20 g/cm3 and B/C = 1.7. This is attributed to a more intense energetic bombardment during deposition and more complete dissociation of the TEB molecule in the plasma at higher plasma power. The hydrogen content in the films ranges between 14 and 20 at. %. Optical emission spectroscopy of the plasma shows that BH, CH, C2, and H are the optically active plasma species from TEB. We suggest a plasma chemical model based on ß-hydrogen elimination of C2H4 to form BH3, in which BH3 and C2H4 are then dehydrogenated to form BH and C2H2. Furthermore, C2H2 decomposes in the plasma to produce C2 and CH, which together with BH and possibly BH3-x(C2H5)x are the film forming species.

Comparing and Correcting Spectral Sensitivities between Multispectral Microscopes: A Prerequisite to Clinical Implementation.

Multispectral, multiplex immunofluorescence (mIF) microscopy has been used to great effect in research to identify cellular co-expression profiles and spatial relationships within tissue, providing a myriad of diagnostic advantages. As these technologies mature, it is essential that image data from mIF microscopes is reproducible and standardizable across devices. We sought to characterize and correct differences in illumination intensity and spectral sensitivity between three multispectral microscopes. We scanned eight melanoma tissue samples twice on each microscope and calculated their average tissue region flux intensities. We found a baseline average standard deviation of 29.9% across all microscopes, scans, and samples, which was reduced to 13.9% after applying sample-specific corrections accounting for differences in the tissue shown on each slide. We used a basic calibration model to correct sample- and microscope-specific effects on overall brightness and relative brightness as a function of the image layer. We tested the generalizability of the calibration procedure and found that applying corrections to independent validation subsets of the samples reduced the variation to 2.9 ± 0.03%. Variations in the unmixed marker expressions were reduced from 15.8% to 4.4% by correcting the raw images to a single reference microscope. Our findings show that mIF microscopes can be standardized for use in clinical pathology laboratories using a relatively simple correction model.

Characterizing the dynamic and functional DNA methylation landscape in the developing human cortex.

DNA methylation (DNAm) is a key epigenetic regulator of gene expression across development. The developing prenatal brain is a highly dynamic tissue, but our understanding of key drivers of epigenetic variability across development is limited. We, therefore, assessed genomic methylation at over 39 million sites in the prenatal cortex using whole-genome bisulfite sequencing and found loci and regions in which methylation levels are dynamic across development. We saw that DNAm at these loci was associated with nearby gene expression and enriched for enhancer chromatin states in prenatal brain tissue. Additionally, these loci were enriched for genes associated with neuropsychiatric disorders and genes involved with neurogenesis. We also found autosomal differences in DNAm between the sexes during prenatal development, though these have less clear functional consequences. We lastly confirmed that the dynamic methylation at this critical period is specifically CpG methylation, with generally low levels of CpH methylation. Our findings provide detailed insight into prenatal brain development as well as clues to the pathogenesis of psychiatric traits seen later in life.

Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk.

DNA methylation (DNAm) is an epigenetic regulator of gene expression and a hallmark of gene-environment interaction. Using whole-genome bisulfite sequencing, we have surveyed DNAm in 344 samples of human postmortem brain tissue from neurotypical subjects and individuals with schizophrenia. We identify genetic influence on local methylation levels throughout the genome, both at CpG sites and CpH sites, with 86% of SNPs and 55% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting the genes and regions with which these loci are epigenetically associated. These findings can be used to better characterize schizophrenia GWAS-identified variants as epigenetic risk variants. Regions differentially methylated by schizophrenia risk-SNPs explain much of the heritability associated with risk loci, despite covering only a fraction of the genomic space. We provide a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain.

Analysis of multispectral imaging with the AstroPath platform informs efficacy of PD-1 blockade.

Next-generation tissue-based biomarkers for immunotherapy will likely include the simultaneous analysis of multiple cell types and their spatial interactions, as well as distinct expression patterns of immunoregulatory molecules. Here, we introduce a comprehensive platform for multispectral imaging and mapping of multiple parameters in tumor tissue sections with high-fidelity single-cell resolution. Image analysis and data handling components were drawn from the field of astronomy. Using this "AstroPath" whole-slide platform and only six markers, we identified key features in pretreatment melanoma specimens that predicted response to anti-programmed cell death-1 (PD-1)-based therapy, including CD163+PD-L1- myeloid cells and CD8+FoxP3+PD-1low/mid T cells. These features were combined to stratify long-term survival after anti-PD-1 blockade. This signature was validated in an independent cohort of patients with melanoma from a different institution.

Interactive imagery and colour in paired-associate learning.

In four experiments participants were instructed to imagine scenes that described either an animal interacting with a coloured object or scenes in which the animal and coloured object were independent of each other. Participants were then given the name of the animal and required to select the name of the object and its colour. The results showed that the classic interactive imagery effect was greater for the selection of the name of the object than it was for colour. In Experiments 2, 3, and 4, additional measures were taken which suggest that the effect for colour is dependent upon the retrieval of other features of the object (e.g., its form). Thus it is argued that there is no primary interactive imagery effect for colour. The results were predicted by a version of the shared information hypothesis. The implications of the results for alternative theories are also considered.

Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space.

When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU) hardware.We followed this approach in implementing a read aligner called Arioc that uses GPU-based parallel sort and reduction techniques to identify high-priority locations where potential alignments may be found. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments found by several leading read aligners. With simulated reads, Arioc has comparable or better accuracy than the other read aligners we tested. With human sequencing reads, Arioc demonstrates significantly greater throughput than the other aligners we evaluated across a wide range of sensitivity settings. The Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.

Erratum: A novel small-angle neutron scattering detector geometry. Corrigendum.

Errors in the paper by Kanaki, Jackson, Hall-Wilton, Piscitelli, Kirstein & Andersen [J. Appl. Cryst. (2013), 46, 1031-1037] are corrected.[This corrects the article DOI: 10.1107/S0021889813011862.].

A novel small-angle neutron scattering detector geometry.

A novel 2π detector geometry for small-angle neutron scattering (SANS) applications is presented and its theoretical performance evaluated. Such a novel geometry is ideally suited for a SANS instrument at the European Spallation Source (ESS). Motivated by the low availability and high price of 3He, the new concept utilizes gaseous detectors with 10B as the neutron converter. The shape of the detector is inspired by an optimization process based on the properties of the conversion material. Advantages over the detector geometry traditionally used on SANS instruments are discussed. The angular and time resolutions of the proposed detector concept are shown to satisfy the requirements of the particular SANS instrument.

The effect of relations in paired-associate learning.

Previous studies have shown that the cued recall of paired associates is greater when one member of a pair has been apprehended as lying on the other member, as compared with the two having been apprehended as independent objects. The effect occurs when the objects have been perceived, imagined, or described in the relevant relationship. The additional thoughts hypothesis postulates that participants have more spontaneous "additional thoughts" when apprehending a pair in the relational condition. These may provide additional retrieval routes, thereby explaining the effect. In four experiments, the hypothesis was tested under conditions in which a clear unambiguous definition could be specified for an additional thought. The results showed that the greater recall in an "on" condition, as compared with an independent condition, occurs at least in part because more additional thoughts occur in the "on" condition. There was no evidence for any other contribution to the effect. It is argued that the findings question whether relations between objects play a fundamental role in the structure of memory.