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      Simultaneous sequencing of genetic and epigenetic bases in DNA

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      Nature Biotechnology
      Nature Publishing Group US
      Epigenomics, Cancer genomics

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          Abstract

          DNA comprises molecular information stored in genetic and epigenetic bases, both of which are vital to our understanding of biology. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases fail to capture common C-to-T mutations or distinguish 5-methylcytosine from 5-hydroxymethylcytosine. We present a single base-resolution sequencing methodology that sequences complete genetics and the two most common cytosine modifications in a single workflow. DNA is copied and bases are enzymatically converted. Coupled decoding of bases across the original and copy strand provides a phased digital readout. Methods are demonstrated on human genomic DNA and cell-free DNA from a blood sample of a patient with cancer. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. Simultaneous, phased reading of genetic and epigenetic bases provides a more complete picture of the information stored in genomes and has applications throughout biomedicine.

          Abstract

          A six-letter sequencing workflow can simultaneously detect genetic and epigenetic bases.

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          fastp: an ultra-fast all-in-one FASTQ preprocessor

          Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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            Twelve years of SAMtools and BCFtools

            Abstract Background SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling, and effect analysis amongst other methods. Findings The first version appeared online 12 years ago and has been maintained and further developed ever since, with many new features and improvements added over the years. The SAMtools and BCFtools packages represent a unique collection of tools that have been used in numerous other software projects and countless genomic pipelines. Conclusion Both SAMtools and BCFtools are freely available on GitHub under the permissive MIT licence, free for both non-commercial and commercial use. Both packages have been installed >1 million times via Bioconda. The source code and documentation are available from https://www.htslib.org.
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              deepTools2: a next generation web server for deep-sequencing data analysis

              We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de. The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.
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                Author and article information

                Contributors
                Joanna.holbrook@cegx.co.uk
                sb10031@cam.ac.uk
                Journal
                Nat Biotechnol
                Nat Biotechnol
                Nature Biotechnology
                Nature Publishing Group US (New York )
                1087-0156
                1546-1696
                6 February 2023
                6 February 2023
                2023
                : 41
                : 10
                : 1457-1464
                Affiliations
                [1 ]Cambridge Epigenetix Ltd, The Trinity Building, Chesterford Research Park, Cambridge, UK
                [2 ]GRID grid.5335.0, ISNI 0000000121885934, Cancer Research UK Cambridge Institute, , University of Cambridge, ; Cambridge, UK
                [3 ]Yusuf Hamied Department of Chemistry, University of Cambridge, ( https://ror.org/013meh722) Cambridge, UK
                Author information
                http://orcid.org/0000-0001-8329-9228
                http://orcid.org/0000-0002-2005-2516
                http://orcid.org/0000-0002-0635-0015
                http://orcid.org/0000-0001-6688-7714
                http://orcid.org/0000-0002-0498-4356
                http://orcid.org/0000-0003-1791-6894
                http://orcid.org/0000-0002-0281-5815
                Article
                1652
                10.1038/s41587-022-01652-0
                10567558
                36747096
                a4c9e63f-8bb1-4f66-8b0b-356c7ca1eac4
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 August 2022
                : 16 December 2022
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                © Springer Nature America, Inc. 2023

                Biotechnology
                epigenomics,cancer genomics
                Biotechnology
                epigenomics, cancer genomics

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