Spurious Alignment Research Articles

Automatic conditioning of marine seismic angle stack data with a convolutional neural network

Misalignment of reflections is a common problem in migrated prestack seismic data, which occurs due to moveout correction with incomplete knowledge of the velocity model. This issue persists in partial angle stack data often used for amplitude-variation-with offset (AVO) analyses and is traditionally treated with residual moveout (RMO) and trim static corrections. However, these methods require time-consuming velocity selection and parameter tuning and commonly lead to spurious alignment of reflections with noise. Therefore, we train a convolutional neural network (CNN) on synthetic examples to automatically perform conditioning and alignment of angle stack data. First, 2D synthetic common-depth point gathers are created using a convolutional modeling method and then made into input-target pairs, where the inputs are poorly moveout corrected (using inaccurate normal-moveout velocities) and the targets are accurately moveout corrected. These input-target examples are split into angle stacks for the near, mid, and far offsets and then used to train a CNN to transform the misaligned angle stacks into their more-aligned counterparts. In testing, the trained network increases the alignment of unseen synthetic data, improving the correlation with the target far-offset trace from 0.76 to 0.85 on average. The network is applied on two field examples from offshore Norway with class 3 and class 2P AVO responses, respectively. In both cases, the angle stack data predicted by the network indicate improved alignment, greater resolution in the far-offset stacked section, and increased correspondence to a well-tie synthetic seismogram, all while retaining the AVO responses. The CNN predictions are compared with angle stack data after traditional conditioning (RMO and trim static corrections), with the results being of similar or greater quality. This method enables high-quality conditioning of angle stack data at a fraction of the time required for conventional methods and is easily adaptable to different data sets.

Unravelling reference bias in ancient DNA datasets.

The alignment of sequencing reads is a critical step in the characterization of ancient genomes. However, reference bias and spurious mappings pose a significant challenge, particularly as cutting-edge wet lab methods generate datasets that push the boundaries of alignment tools. Reference bias occurs when reference alleles are favoured over alternative alleles during mapping, whereas spurious mappings stem from either contamination or when endogenous reads fail to align to their correct position. Previous work has shown that these phenomena are correlated with read length but a more thorough investigation of reference bias and spurious mappings for ancient DNA has been lacking. Here, we use a range of empirical and simulated palaeogenomic datasets to investigate the impacts of mapping tools, quality thresholds, and reference genome on mismatch rates across read lengths. For these analyses, we introduce AMBER, a new bioinformatics tool for assessing the quality of ancient DNA mapping directly from BAM-files and informing on reference bias, read length cut-offs and reference selection. AMBER rapidly and simultaneously computes the sequence read mapping bias in the form of the mismatch rates per read length, cytosine deamination profiles at both CpG and non-CpG sites, fragment length distributions, and genomic breadth and depth of coverage. Using AMBER, we find that mapping algorithms and quality threshold choices dictate reference bias and rates of spurious alignment at different read lengths in a predictable manner, suggesting that optimized mapping parameters for each read length will be a key step in alleviating reference bias and spurious mappings. AMBER is available for noncommercial use on GitHub (https://github.com/tvandervalk/AMBER.git). Scripts used to generate and analyse simulated datasets are available on Github (https://github.com/sdolenz/refbias_scripts).

O-103 A method for mapping sex-specific meiotic crossovers from PGT-A data elucidates the role of aberrant recombination in the origins of aneuploidy

Abstract Study question How do the number and location of meiotic crossovers contribute to the formation of aneuploidies observed in preimplantation human embryos? Summary answer Normalized across chromosomes, trisomies possess 35% fewer crossovers on average compared to disomies, while the genomic distribution of crossovers is also substantially altered. What is known already Meiotic recombination is a crucial source of genetic diversity and is also critical for ensuring the accuracy of chromosome segregation. Understanding the landscape of meiotic recombination, its variation across individuals, and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring the landscape of recombination either rely on population genetic patterns of linkage disequilibrium—capturing a time-averaged view—or direct detection of crossovers in gametes or multi-generation pedigrees, limiting the scale and availability of relevant datasets. Moreover, most of these methods are designed for discovering recombination using data from normal, disomic chromosomes. Study design, size, duration We present a method for mapping sex-specific recombination landscapes from low-coverage (<0.1×) data from preimplantation genetic testing for aneuploidy (PGT-A) of embryos with arbitrary ploidy configurations. To overcome the sparsity of these data, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, as well as the frequent occurrence of chromosome loss in embryos, whereby the remaining chromosome is phased by default. Participants/materials, setting, methods We benchmarked our method by simulating crossovers between known haplotypes. Encouraged by the performance on simulated data we extended our study to retrospective analysis utilizing de-identified PGT-A data obtained between April 2021 and August 2022 at the CReATe Fertility Centre (Toronto, Canada). The data include 20,160 embryos (2,559 IVF patients) with an average depth of coverage of ∼0.05×, facilitating the mapping of crossovers at an average resolution of ∼150 kbp. Main results and the role of chance Our benchmarking results demonstrate high sensitivity and specificity across all ancestries at a coverage of 0.05x per homolog (AUC = 0.989), with AUC declining by 0.014 and 0.053 for when coverage is reduced to 0.025x and 0.013x, respectively. Extending our analysis to real PGT-A data, we observed that our inferred sex-specific landscapes of meiotic crossovers on disomic chromosomes were strongly correlated with published genetic maps from studies based on high-coverage sequencing of parent-offspring trios (r = 0.86 for female map; r = 0.53 for male map), broadly supporting the accuracy of our method. Notably, the total length of the female genetic map was reduced by 35% for trisomies compared to disomies, consistent with the hypothesized role of reduced crossovers and exchangeless chromosomes in the origins of female meiotic aneuploidy. In addition, the genomic distribution of crossovers is also altered in a chromosome-specific manner. Examples include a reduction in crossovers near the centromere of trisomies versus disomies of chromosome 16, as well as an enrichment of crossovers on the q-arm of trisomies versus disomies of chromosome 22. Together, our results provide a detailed corroboration of the hypothesis that aberrant meiotic recombination contributes to the origins of aneuploidies. Limitations, reasons for caution The accuracy of our method is influenced by genomic heterogeneity in depth of coverage, rates of heterozygosity, and mismatches between the ancestry of the reference panel and the tested sequence. Moreover, technical errors such as spurious alignment and genotyping could hinder analysis in repetitive genomic regions. Wider implications of the findings Together, our study helps clarify the dual function of meiotic recombination in generating genetic diversity while ensuring meiotic fidelity. Our method for patient-specific mapping of meiotic recombination phenotypes may offer clues about how dysregulation of this process contributes to infertility. Trial registration number NIH r R35GM13374

Lensing measurements of the ellipticity of luminous red galaxies dark matter haloes

Lensing measurements of the shapes of dark matter halos can provide tests of gravity theories and possible dark matter interactions. We measure the quadrupole weak lensing signal from the elliptical halos of 70,000 SDSS Luminous Red Galaxies. We use a new estimator that nulls the spherical halo lensing signal, isolating the shear due to anisotropy in the dark matter distribution. One of the two Cartesian components of our estimator is insensitive to the primary systematic, a spurious alignment of lens and source ellipticities, allowing us to make robust measurements of halo ellipticity. Our best-fit value for the ellipticity of the surface mass density is $0.24 \pm 0.06$, which translates to an axis ratio of 0.78. We rule out the hypothesis of no ellipticity at the $4\sigma$ confidence level, and ellipticity < 0.12 (axis ratio > 0.89) at the $2\sigma$ level. We discuss how our measurements of halo ellipticity are revised to higher values using estimates of the misalignment of mass and light from simulations. Finally, we apply the same techniques to a smaller sample of redMaPPer galaxy clusters and obtain a $3\sigma$ measurement of cluster ellipticity. We discuss how the improved signal to noise properties of our estimator can enable studies of halo shapes for different galaxy populations with upcoming surveys.

Oil Recovery Increased by Use of Event Detection and Association

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 167836, ’From Market-Basket Analysis to Wellhead Monitoring: Use of Events To Increase Oil Recovery,’ by R. Bailey, Z. Lu, S. Shirzadi, and E. Ziegel, BP, prepared for the 2014 SPE Intelligent Energy Conference and Exhibition, Utrecht, The Netherlands, 1-3 April. The paper has not been peer reviewed. An operator has launched a successful, limited-scope deployment of a nonparametric capability known as event detection and association (EDA). Variations from the original analytical approach may be necessary before the EDA techniques can be used to solve problems in the field. EDA comprises part of a suite of tools collectively referred to as topdown waterflood (TDWF) diagnostic and optimization. By studying the time-based correlation of these input and output events, the basic TDWF capacitance/resistivity model is either confirmed or improved. Introduction It is almost an automatic response for the human mind, presented with time-series data such as controller strip charts, to seek features in those data, mentally label them as “events,” and seek correlations in time against other timelines. However, the human mind is not only highly capable, it is all too often fallible. It will favor connections with short time lags and events of the same shape, size, and duration, paying little attention to the influence on shape of variable scaling. It will also tend to associate variables for which it has a preconceived notion that relationships exist while failing to assess the statistical validity of the labeling process. The mind’s eye can be persuaded easily by superposition and purposeful or even spurious alignment of individual tags’ time traces. Such visual tricks help to find supporting evidence for a pattern. The real challenge is development of an automated, comprehensive, dispassionate, independent, statistically valid process. If all these objectives can be met, then many types of oilfield evaluations can be carried out using an event-based analysis. The Event-Based Approach A Brief Description. For an asset that is being studied, one must first choose the producer and injector wells to include in the study. These will be wells that are sufficiently well instrumented to provide a time-series data stream expected to contain events that are discernible from the unavoidable sources of measurement noise. Next, one will choose a time period to be the focus of the analysis. Recent data are more likely to be most instructive in regard to what is likely to happen next, but better-quality periods of data may exist. Then, one must choose the well attribute that will be used as the variable that will indicate the occurrence of an event. Typically, the choice will be an allocated (or possibly measured) flow, an aspect of production such as water cut or gas/oil ratio, or a direct intensive measurement such as a pressure or even a temperature. Similarly, injector wells will have some (typically) corresponding attribute, such as injection rate or some pressure. The event-based analysis begins with the marking of events for each producer and injector well. The authors have developed an automated event-marking algorithm. Once a complete set of injection and production events has been obtained, the process associates these events with each other. This is performed by considering an appropriate range of time delays that reflect the physical separation of the wells and the intervening reservoir properties. The result is a ranking of the connections considered possible between injectors and producers, together with their estimated time delays, and is summarized as an optimal score for each connection.

Coval: Improving Alignment Quality and Variant Calling Accuracy for Next-Generation Sequencing Data

Accurate identification of DNA polymorphisms using next-generation sequencing technology is challenging because of a high rate of sequencing error and incorrect mapping of reads to reference genomes. Currently available short read aligners and DNA variant callers suffer from these problems. We developed the Coval software to improve the quality of short read alignments. Coval is designed to minimize the incidence of spurious alignment of short reads, by filtering mismatched reads that remained in alignments after local realignment and error correction of mismatched reads. The error correction is executed based on the base quality and allele frequency at the non-reference positions for an individual or pooled sample. We demonstrated the utility of Coval by applying it to simulated genomes and experimentally obtained short-read data of rice, nematode, and mouse. Moreover, we found an unexpectedly large number of incorrectly mapped reads in ‘targeted’ alignments, where the whole genome sequencing reads had been aligned to a local genomic segment, and showed that Coval effectively eliminated such spurious alignments. We conclude that Coval significantly improves the quality of short-read sequence alignments, thereby increasing the calling accuracy of currently available tools for SNP and indel identification. Coval is available at http://sourceforge.net/projects/coval105/.

Improving syntactic rule extraction through deleting spurious links with translation span alignment

AbstractMost statistical machine translation systems typically rely on word alignments to extract translation rules. This approach would suffer from a practical problem that even one spurious word alignment link can prevent some desirable translation rules from being extracted. To address this issue, this paper presents two approaches, referred to as sub-tree alignment and phrase-based forced decoding methods, to automatically learn translation span alignments from parallel data. Then, we improve the translation rule extraction by deleting spurious links and inserting new links based on bilingual translation span correspondences. Some comparison experiments are designed to demonstrate the effectiveness of the proposed approaches.

Galaxy alignments in very X-ray luminous clusters at z &gt; 0.5

We present the results of a search for galaxy alignments in 12 galaxy clusters at z>0.5, a statistically complete subset of the very X-ray luminous clusters from the MAssive Cluster Survey (MACS). Using high-quality images taken with the Hubble Space Telescope (HST) that render measurement errors negligible, we find no radial galaxy alignments within 500 kpc of the cluster centres for a sample of 545 spectroscopically confirmed cluster members. A mild, but statistically insignificant trend favouring radial alignments is observed within a radius of 200 kpc and traced to galaxies on the cluster red sequence. Our results for massive clusters at z>0.5 are in stark contrast to the findings of previous studies which find highly significant radial alignments of galaxies in nearby clusters at z~0.1 out to at least half the virial radius using imaging data from the SDSS. The discrepancy becomes even more startling if radial alignment becomes more prevalent at decreasing clustercentric distance, as suggested by both our and previous work. We investigate and discuss potential causes for the disparity between our findings based on HST images of clusters at z>0.5 and those obtained using groundbased images of systems at z~0.1. We conclude that the most likely explanation is either dramatic evolution with redshift (in the sense that radial alignments are less pronounced in dynamically younger systems) or the presence of systematic biases in the analysis of SDSS imaging data that cause at least partly spurious alignment signals.

DISCOVERY OF A LARGE-SCALE GALAXY FILAMENT NEAR A CANDIDATE INTERGALACTIC X-RAY ABSORPTION SYSTEM

We present an analysis of the large-scale galaxy distribution around two possible warm-hot intergalactic medium (WHIM) absorption systems reported along the Markarian 421 sightline. Using the Sloan Digital Sky Survey, we find a prominent galaxy filament at the redshift of the z=0.027 X-ray absorption line system. The filament exhibits a width of 3.2 Mpc and length of at least 20 Mpc, comparable to the size of WHIM filaments seen in cosmological simulations. No individual galaxies fall within 350 projected kpc so it is unlikely that the absorption is associated with gas in a galaxy halo or outflow. Another, lower-significance X-ray absorption system was reported in the same Chandra spectrum at z=0.011, but the large-scale structure in its vicinity is far weaker and may be a spurious alignment. By searching for similar galaxy structures in 140 random smoothed SDSS fields, we estimate a ~5-10% probability of the z=0.027 absorber-filament alignment occurring by chance. If these two systems are indeed physically associated, this would represent the first known coincidence between large-scale galaxy structure and a blind X-ray WHIM detection.

Parameters for accurate genome alignment

BackgroundGenome sequence alignments form the basis of much research. Genome alignment depends on various mundane but critical choices, such as how to mask repeats and which score parameters to use. Surprisingly, there has been no large-scale assessment of these choices using real genomic data. Moreover, rigorous procedures to control the rate of spurious alignment have not been employed.ResultsWe have assessed 495 combinations of score parameters for alignment of animal, plant, and fungal genomes. As our gold-standard of accuracy, we used genome alignments implied by multiple alignments of proteins and of structural RNAs. We found the HOXD scoring schemes underlying alignments in the UCSC genome database to be far from optimal, and suggest better parameters. Higher values of the X-drop parameter are not always better. E-values accurately indicate the rate of spurious alignment, but only if tandem repeats are masked in a non-standard way. Finally, we show that γ-centroid (probabilistic) alignment can find highly reliable subsets of aligned bases.ConclusionsThese results enable more accurate genome alignment, with reliability measures for local alignments and for individual aligned bases. This study was made possible by our new software, LAST, which can align vertebrate genomes in a few hours http://last.cbrc.jp/.

The whole alignment and nothing but the alignment: the problem of spurious alignment flanks

Pairwise sequence alignment is a ubiquitous tool for inferring the evolution and function of DNA, RNA and protein sequences. It is therefore essential to identify alignments arising by chance alone, i.e. spurious alignments. On one hand, if an entire alignment is spurious, statistical techniques for identifying and eliminating it are well known. On the other hand, if only a part of the alignment is spurious, elimination is much more problematic. In practice, even the sizes and frequencies of spurious subalignments remain unknown. This article shows that some common scoring schemes tend to overextend alignments and generate spurious alignment flanks up to hundreds of base pairs/amino acids in length. In the UCSC genome database, e.g. spurious flanks probably comprise >18% of the human–fugu genome alignment. To evaluate the possibility that chance alone generated a particular flank on a particular pairwise alignment, we provide a simple ‘overalignment’ P-value. The overalignment P-value can identify spurious alignment flanks, thereby eliminating potentially misleading inferences about evolution and function. Moreover, by explicitly demonstrating the tradeoff between over- and under-alignment, our methods guide the rational choice of scoring schemes for various alignment tasks.

Ellipticity of dark matter haloes with galaxy-galaxy weak lensing

We present the results of attempts to detect the ellipticity of dark matter haloes using galaxy-galaxy weak lensing with Sloan Digital Sky Survey (SDSS) data. We use 2020256 galaxies brighter than r = 19 with photometric redshifts (divided into colour and luminosity sub-samples) as lenses and 31 697 869 source galaxies. We search for and identify several signal contaminants, which if not removed lead to a spurious detection. These include systematic shear that leads to a slight spurious alignment of lens and source ellipticities, intrinsic alignments (due to contamination of the source sample by physically associated lens-source pairs). and anisotropic magnification bias. We develop methods that allow us to remove these contaminants to the signal. We split the analysis into blue (spiral) and red (elliptical) galaxies. Assuming Gaussian errors as in previous work and a power-law profile, we find f h = e h /e g = 0.1 ± 0.06 for red galaxies and -0.8 ± 0.4 for blue galaxies, using transverse separations of 20-300 h -1 kpc, averaged over luminosity. Inclusion of the more realistic non-Gaussian error distributions and of the Navarro-Frenk-White (NFW) density profile (which predicts much smaller ellipticity of the shear for scales above the scale radius) yields 0.60 ± 0.38 for ellipticals and -1.4 +1.7 -2.0 for spirals. While there is no concrete detection of alignment in either case, there is a suggestion in the data of a positive alignment in the brightest lens sample of ellipticals. Our results appear to be mildly inconsistent with a previously reported detection by Hoekstra, Yee & Gladders, but more data and further tests are needed to clarify whether4 the discrepancy is real or a consequence of differences in the lens galaxy samples used and analysis methods.

The Morphology of the Emission-Line Region Of Compact Steep-Spectrum Radio Sources

We present the results of HST narrowband imaging of 11 compact steep-spectrum (CSS) radio sources. Five of them (3C 48, 3C 147, 3C303.1, 3C 277.1, and 4C 12.50) were observed as part of a dedicated pointed program of deep line imaging, at the redshifted wavelength of the [O III] λ5007 emission line. For six additional sources (3C 49, 3C 93.1, 3C 138, 3C 268.3, 3C305.1, and 3C343.1) images ([O III] λ5007 or [O II] λ3727) were taken from the HST archive. In all but one of the targets (3C 49) line emission has been detected, and only in the case of 3C 138 is it unresolved at the HST resolution. Three distinct components are found in the CSS emission-line morphologies: (1) compact nuclear emission regions whose size is less than a few kpc, (2) bright emission spatially related to the radio structure, and (3) faint emission that extends well beyond the radio source. A large fraction of the line emission (between 30% and 90%) originates within less than ~3 kpc from the nucleus, as in the case of Seyfert and extended radio galaxies. In four out five of the sources for which deep observations are available, the line emission extends well beyond the size of the radio source but along the radio axis. Only in the case of the largest radio source (3C 277.3) is no emission beyond the radio lobes detected. Structures of similar surface brightness would have not been seen in the snapshot images. These emission-line structures extend to scales of 10 to 30 kpc and cover a projected angle, when seen from the nucleus, of ~30° to 110°, and they indicate that the nuclear illumination is anisotropic. Photon-counting arguments also support this interpretation. In agreement with the AGN unified scheme, only the CSSs with broad line regions show a strong unresolved continuum source in the HST images. In six objects the radio emission extends over more than 1'' and the HST resolution is such that a detailed comparison can be made between radio and optical morphologies. In these cases the line emission has an elongated structure, linking the nucleus to the radio lobes, possibly tracing the path of the invisible radio jets. Nevertheless, the emission-line morphologies do not show the bow shocks at the extremities of the radio lobes one would expect if they are sources whose expansion is frustrated by a dense external medium. Our data favor the alternative model in which CSSs are the young phase of the large-size radio sources. When pointed pure continuum images are available, there appears to be no alignment between radio and continuum emission, which contradicts previous suggestions based on broadband HST imaging. We suggest that these broadband images are in most cases heavily contaminated by line emission, producing a spurious apparent alignment.