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1. PhyloWGA : chromosome-aware phylogenetic interrogation of whole genome alignments

   https://doi.org/10.1093/bioinformatics/btaa884  

   Adams, Richard H; Castoe, Todd A; DeGiorgio, Michael (December 2020, Bioinformatics)

   Ponty, Yann (Ed.)

   Abstract Summary Here, we present PhyloWGA, an open source R package for conducting phylogenetic analysis and investigation of whole genome data. Availabilityand implementation Available at Github (https://github.com/radamsRHA/PhyloWGA). Supplementary information Supplementary data are available at Bioinformatics online. 

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2. U-PASS: unified power analysis and forensics for qualitative traits in genetic association studies

   https://doi.org/10.1093/bioinformatics/btz637  

   Gao, Zheng; Terhorst, Jonathan; Van Hout, Cristopher V.; Stoev, Stilian; Schwartz, ed., Russell (August 2019, Bioinformatics)

   Abstract SummaryDespite the availability of existing calculators for statistical power analysis in genetic association studies, there has not been a model-invariant and test-independent tool that allows for both planning of prospective studies and systematic review of reported findings. In this work, we develop a web-based application U-PASS (Unified Power analysis of ASsociation Studies), implementing a unified framework for the analysis of common association tests for binary qualitative traits. The application quantifies the shared asymptotic power limits of the common association tests, and visualizes the fundamental statistical trade-off between risk allele frequency and odds ratio. The application also addresses the applicability of asymptotics-based power calculations in finite samples, and provides guidelines for single-SNP-based association tests. In addition to designing prospective studies, U-PASS enables researchers to retrospectively assess the statistical validity of previously reported associations. Availability and implementationU-PASS is an open-source R Shiny application. A live instance is hosted at https://power.stat.lsa.umich.edu. Source is available on https://github.com/Pill-GZ/U-PASS. Supplementary informationSupplementary data are available at Bioinformatics online. 

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3. ProDy 2.0: increased scale and scope after 10 years of protein dynamics modelling with Python

   https://doi.org/10.1093/bioinformatics/btab187  

   Zhang, She; Krieger, James M; Zhang, Yan; Kaya, Cihan; Kaynak, Burak; Mikulska-Ruminska, Karolina; Doruker, Pemra; Li, Hongchun; Bahar, Ivet (April 2021, Bioinformatics)

   Cowen, Lenore (Ed.)

   Abstract Summary ProDy, an integrated application programming interface developed for modelling and analysing protein dynamics, has significantly evolved in recent years in response to the growing data and needs of the computational biology community. We present major developments that led to ProDy 2.0: (i) improved interfacing with databases and parsing new file formats, (ii) SignDy for signature dynamics of protein families, (iii) CryoDy for collective dynamics of supramolecular systems using cryo-EM density maps and (iv) essential site scanning analysis for identifying sites essential to modulating global dynamics. Availability and implementation ProDy is open-source and freely available under MIT License from https://github.com/prody/ProDy. Supplementary information Supplementary data are available at Bioinformatics online. 

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4. Optimal gap-affine alignment in O ( s ) space

   https://doi.org/10.1093/bioinformatics/btad074  

   Marco-Sola, Santiago; Eizenga, Jordan M; Guarracino, Andrea; Paten, Benedict; Garrison, Erik; Moreto, Miquel (February 2023, Bioinformatics)

   Martelli, Pier Luigi (Ed.)

   Abstract MotivationPairwise sequence alignment remains a fundamental problem in computational biology and bioinformatics. Recent advances in genomics and sequencing technologies demand faster and scalable algorithms that can cope with the ever-increasing sequence lengths. Classical pairwise alignment algorithms based on dynamic programming are strongly limited by quadratic requirements in time and memory. The recently proposed wavefront alignment algorithm (WFA) introduced an efficient algorithm to perform exact gap-affine alignment in O(ns) time, where s is the optimal score and n is the sequence length. Notwithstanding these bounds, WFA’s O(s2) memory requirements become computationally impractical for genome-scale alignments, leading to a need for further improvement. ResultsIn this article, we present the bidirectional WFA algorithm, the first gap-affine algorithm capable of computing optimal alignments in O(s) memory while retaining WFA’s time complexity of O(ns). As a result, this work improves the lowest known memory bound O(n) to compute gap-affine alignments. In practice, our implementation never requires more than a few hundred MBs aligning noisy Oxford Nanopore Technologies reads up to 1 Mbp long while maintaining competitive execution times. Availability and implementationAll code is publicly available at https://github.com/smarco/BiWFA-paper. Supplementary informationSupplementary data are available at Bioinformatics online. 

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5. eMPRess: a systematic cophylogeny reconciliation tool

   https://doi.org/10.1093/bioinformatics/btaa978  

   Santichaivekin, Santi; Yang, Qing; Liu, Jingyi; Mawhorter, Ross; Jiang, Justin; Wesley, Trenton; Wu, Yi-Chieh; Libeskind-Hadas, Ran (November 2020, Bioinformatics)

   Russell, Schwartz (Ed.)

   Abstract Summary We describe eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences. Availability and implementation eMPRess is freely available at http://www.cs.hmc.edu/empress. Supplementary information Supplementary data are available at Bioinformatics online. 

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