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1. Dynamic time warping of palaeomagnetic secular variation data

   https://doi.org/10.1093/gji/ggaa004  

   Hagen, Cedric J; Reilly, Brendan T; Stoner, Joseph S; Creveling, Jessica R (April 2020, Geophysical Journal International)

   SUMMARY We present and make publicly available a dynamic programming algorithm to simultaneously align the inclination and declination vector directions of sedimentary palaeomagnetic secular variation data. This algorithm generates a library of possible alignments through the systematic variation of assumptions about the relative accumulation rate and shared temporal overlap of two or more time-series. The palaeomagnetist can then evaluate this library of reproducible and objective alignments using available geological constraints, statistical methods and expert knowledge. We apply the algorithm to align previously (visually) correlated medium to high accumulation rate northern North Atlantic Holocene deposits (101–102 cm ka–1) with strong radiocarbon control. The algorithm generates plausible alignments that largely conform with radiocarbon and magnetic acquisition process uncertainty. These alignments illustrate the strengths and limitations of this numerical approach. 

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2. An algorithm-guided Ediacaran global composite δ13Ccarb–Bayesian age model

   https://doi.org/https://doi.org/10.1016/j.palaeo.2024.112321  

   Hagen, Cedric J; Creveling, Jessica R (September 2024, Palaeogeography palaeoclimatology palaeoecology)

   While it remains uncertain whether excursions in the stable carbon isotopic composition of Ediacaran marine carbonate (δ13Ccarb) represent globally synchronous events (or a direct measure of ocean carbon cycling), the absence of widely distributed and readily preservable fauna, and the presence of several iconic carbon isotope excursions (CIEs), has sustained δ13Ccarb correlation as the primary means to establish relative time relationships for Ediacaran successions. Here we present an Ediacaran global δ13Ccarb composite built with a dynamic time warping (DTW) time-normalization algorithm that generates libraries of least-squares alignments between chemostratigraphic records of unequal length and distinct sediment accumulation rates. When developing a δ13Ccarb composite for each of 16 globally distributed Ediacaran paleo-depositional regions, we selected high Pearson r alignments that conformed with published geological guidance about the correlation of constituent sections. When applying DTW to align these regional algorithmic composites into one global δ13Ccarb stack, we selected alignments that allied the excursions that field workers have established (or speculated) are the Marinoan cap carbonate excursion, the Shuram excursion, and/or the basal Cambrian excursion. There are strengths and weaknesses to making explicit the temporal relationships (point-to-point correspondences) often left implicit in visual correlation. One strength is to extrapolate depositional ages by means of isotopic correlation, and here we explored this with a Bayesian Markov chain Monte Carlo age model that predicts a median age, and uncertainty, for every carbonate stratum in the global Ediacaran δ13Ccarb composite. Yet, one must caution against a false accuracy that can arise from selecting one alignment among many possibilities––the likelihood that time-uncertain time series can be stretched and squeezed into one unequivocal alignment is low. Thus, while these alignments are grounded in the expert assessment of the field worker, this global Ediacaran δ13Ccarb–Bayesian age model should be viewed as a working hypothesis to enrich, but not arbitrate, discussions of the correlation, synchrony, and completeness of Ediacaran successions. 

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3. RCSB protein Data Bank: exploring protein 3D similarities via comprehensive structural alignments

   https://doi.org/10.1093/bioinformatics/btae370  

   Bittrich, Sebastian; Segura, Joan; Duarte, Jose_M; Burley, Stephen_K; Rose, Yana; Elofsson, ed., Arne (June 2024, Bioinformatics)

   Abstract MotivationTools for pairwise alignments between 3D structures of proteins are of fundamental importance for structural biology and bioinformatics, enabling visual exploration of evolutionary and functional relationships. However, the absence of a user-friendly, browser-based tool for creating alignments and visualizing them at both 1D sequence and 3D structural levels makes this process unnecessarily cumbersome. ResultsWe introduce a novel pairwise structure alignment tool (rcsb.org/alignment) that seamlessly integrates into the RCSB Protein Data Bank (RCSB PDB) research-focused RCSB.org web portal. Our tool and its underlying application programming interface (alignment.rcsb.org) empowers users to align several protein chains with a reference structure by providing access to established alignment algorithms (FATCAT, CE, TM-align, or Smith–Waterman 3D). The user-friendly interface simplifies parameter setup and input selection. Within seconds, our tool enables visualization of results in both sequence (1D) and structural (3D) perspectives through the RCSB PDB RCSB.org Sequence Annotations viewer and Mol* 3D viewer, respectively. Users can effortlessly compare structures deposited in the PDB archive alongside more than a million incorporated Computed Structure Models coming from the ModelArchive and AlphaFold DB. Moreover, this tool can be used to align custom structure data by providing a link/URL or uploading atomic coordinate files directly. Importantly, alignment results can be bookmarked and shared with collaborators. By bridging the gap between 1D sequence and 3D structures of proteins, our tool facilitates deeper understanding of complex evolutionary relationships among proteins through comprehensive sequence and structural analyses. Availability and implementationThe alignment tool is part of the RCSB PDB research-focused RCSB.org web portal and available at rcsb.org/alignment. Programmatic access is available via alignment.rcsb.org. Frontend code has been published at github.com/rcsb/rcsb-pecos-app. Visualization is powered by the open-source Mol* viewer (github.com/molstar/molstar and github.com/molstar/rcsb-molstar) plus the Sequence Annotations in 3D Viewer (github.com/rcsb/rcsb-saguaro-3d). 

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4. Sequence Braiding: Visual Overviews of Temporal Event Sequences and Attributes

   https://doi.org/10.1109/TVCG.2020.3030442  

   Bartolomeo, Sara Di; Zhang, Yixuan; Sheng, Fangfang; Dunne, Cody (October 2020, IEEE Transactions on Visualization and Computer Graphics)

   null (Ed.)

   Temporal event sequence alignment has been used in many domains to visualize nuanced changes and interactions over time. Existing approaches align one or two sentinel events. Overview tasks require examining all alignments of interest using interaction and time or juxtaposition of many visualizations. Furthermore, any event attribute overviews are not closely tied to sequence visualizations. We present SEQUENCE BRAIDING, a novel overview visualization for temporal event sequences and attributes using a layered directed acyclic network. SEQUENCE BRAIDING visually aligns many temporal events and attribute groups simultaneously and supports arbitrary ordering, absence, and duplication of events. In a controlled experiment we compare SEQUENCE BRAIDING and IDMVis on user task completion time, correctness, error, and confidence. Our results provide good evidence that users of SEQUENCE BRAIDING can understand high-level patterns and trends faster and with similar error. A full version of this paper with all appendices; the evaluation stimuli, data, and analysis code; and source code are available at osf.io/mq2wt. 

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5. Vargas: heuristic-free alignment for assessing linear and graph read aligners

   https://doi.org/10.1093/bioinformatics/btaa265  

   Darby, Charlotte A; Gaddipati, Ravi; Schatz, Michael C; Langmead, Ben; Birol, Inanc (April 2020, Bioinformatics)

   Abstract Motivation Read alignment is central to many aspects of modern genomics. Most aligners use heuristics to accelerate processing, but these heuristics can fail to find the optimal alignments of reads. Alignment accuracy is typically measured through simulated reads; however, the simulated location may not be the (only) location with the optimal alignment score. Results Vargas implements a heuristic-free algorithm guaranteed to find the highest-scoring alignment for real sequencing reads to a linear or graph genome. With semiglobal and local alignment modes and affine gap and quality-scaled mismatch penalties, it can implement the scoring functions of commonly used aligners to calculate optimal alignments. While this is computationally intensive, Vargas uses multi-core parallelization and vectorized (SIMD) instructions to make it practical to optimally align large numbers of reads, achieving a maximum speed of 456 billion cell updates per second. We demonstrate how these “gold standard” Vargas alignments can be used to improve heuristic alignment accuracy by optimizing command-line parameters in Bowtie 2, BWA-MEM, and vg to align more reads correctly. Availability and implementation Source code implemented in C ++ and compiled binary releases are available at https://github.com/langmead-lab/vargas under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online. 

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