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GB/T 43584.2-2023 English PDF

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GB/T 43584.2-2023: Biotechnology - Massively parallel sequencing - Part 2: Quality evaluation of sequencing data
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GB/T 43584.2-2023English404 Add to Cart 4 days [Need to translate] Biotechnology - Massively parallel sequencing - Part 2: Quality evaluation of sequencing data Valid GB/T 43584.2-2023

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Basic data

Standard ID GB/T 43584.2-2023 (GB/T43584.2-2023)
Description (Translated English) Biotechnology - Massively parallel sequencing - Part 2: Quality evaluation of sequencing data
Sector / Industry National Standard (Recommended)
Classification of Chinese Standard A40
Classification of International Standard 07.080
Word Count Estimation 22,294
Date of Issue 2023-12-28
Date of Implementation 2023-12-28
Issuing agency(ies) State Administration for Market Regulation, China National Standardization Administration

GB/T 43584.2-2023: Biotechnology - Massively parallel sequencing - Part 2: Quality evaluation of sequencing data


---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
ICS 07:080 CCSA40 National Standards of People's Republic of China Massively parallel sequencing in biotechnology Part 2: Quality assessment of sequencing data (ISO 20397-2:2021,IDT) Published on 2023-12-28 Implemented on 2023-12-28 State Administration for Market Regulation Released by the National Standardization Administration Committee

Table of contents

Preface III Introduction IV 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Raw data 5 4:1 General 5 4:2 Raw data files 5 4:3 Quality assessment of raw data 5 4:4 Raw data preprocessing 7 5 Sequence alignment and positioning 7 5:1 General 7 5:2 Sequence alignment and positioning file format 7 5:3 Quality control of sequence alignment and mapping 8 5:4 Post-processing 9 6 Variant identification 9 6:1 General 9 6:2 Data files for variant calling 9 6:3 Quality indicators for variant calling10 6:4 False positive mutation processing 10 6:5 Sequence annotation 10 7 Verify 10 7:1 General 10 7:2 Quality indicator verification10 8 File 11 Appendix A (Informative) Quality Indicators for Specific MPS Platform Examples12 Appendix B (informative) Coverage and recommended reading order by application13 Appendix C (Informative) Sequence Alignment and Positioning Software 14 Reference 15

Foreword

This document complies with the provisions of GB/T 1:1-2020 "Standardization Work Guidelines Part 1: Structure and Drafting Rules of Standardization Documents" Drafting: This document is Part 2 of GB/T 43584 "Massively Parallel Sequencing in Biotechnology": GB/T 43584 has published the following parts: ---Part 2: Quality assessment of sequencing data: This document is equivalent to ISO 20397-2:2021 "Massively parallel sequencing in biotechnology Part 2: Quality assessment of sequencing data" estimate": Please note that some content in this document may be subject to patents: The publisher of this document assumes no responsibility for identifying patents: This document is proposed and coordinated by the National Technical Committee for Standardization of Biochemical Testing (SAC/TC387): This document was drafted by: Institute of Biology, China Academy of Testing Technology, Jianghan University, China Academy of Testing Technology, Shenzhen BGI Life Sciences Academy of Sciences, Hebei Food Inspection Institute, Chengdu Medical College, Shenzhen Huahan Gene Life Technology Co:, Ltd:, Zhejiang Beilanbo Biotechnology Technology Co:, Ltd:, Shenzhen Inspection Group (Shenzhen) Medical Laboratory Laboratory: The main drafters of this document: Zhou Lihua, Li Huaiping, Ye Shanrong, Yi Yan, Wang Dan, Jiang Zhanyue, Wei Xiaofeng, Lin Hua, Fan Dongsheng, Chen Jiaping, Ye Deping, Peng Hai, Feng Shuang, Wang Qi, Ma Lixia, Zhang Yan, Zhang Yong, Yang Jun, Zhang Caimin, Jiang Hui, Yang Guowu:

Introduction

Massively parallel sequencing (MPS) is a high-throughput analysis method for nucleic acid sequencing that utilizes massively parallel processing: Study the whole genome, transcriptome and specific target nucleic acids of different organisms in a relatively short period of time: MPS has been used in many life science fields and can perform determination and high-throughput analysis of millions or even tens of millions of nucleotide bases: born Biological variation in DNA and RNA polymers within the body poses challenges for accurate sequence determination: Measured by MPS, sequence Column quality depends on many factors, including but not limited to sample quality, library preparation, platform selection, and sequencing data quality: GB/T 43584 is intended to consist of the following parts: ---Part 1: Nucleic acid and library preparation: Part 1 mainly provides basic research and aims to provide the prerequisites for sequencing and data generation: General guidelines and considerations for library preparation and library quality assessment: ---Part 2: Quality assessment of sequencing data: Part 2 carries out specific operations and data quality control based on Part 1 and provides Part 3 provides the basis for the research: ---Part 3: General requirements and guidelines for metagenomics: Part 3 includes Part 1 and Part 2, and stipulates macrogenes Omics guidelines from sample preparation, generation and analysis of sequencing data: Sequencing data analysis poses major challenges to bioinformatics in many areas such as data storage, computing time, and mutation detection accuracy: war: One of the major challenges associated with sequencing data is monitoring quality control metrics at all stages of the data processing pipeline, which can easily be overlooked: Understanding data quality is critical to downstream sequence analysis: Quality control of nucleic acid sequencing data processing and analysis can be divided into three stages: original Data, alignment and variant identification: This document provides precautions for MPS sequencing data quality assessment, as well as instructions for different MPS platforms: The station provides specific suggestions: Massively parallel sequencing in biotechnology Part 2: Quality assessment of sequencing data

1 Scope

This document clarifies the overall requirements and recommendations for quality assessment of massively parallel sequencing data: Covers the post-generation of raw data Programs, sequence alignment and variant calling: This document provides general guidance for the validation and archiving of massively parallel sequencing (MPS) data: This document does not apply to any processing associated with de novo assembly:

2 Normative reference documents

This document has no normative references:

3 Terms and definitions

The following terms and definitions apply to this document: 3:1 adapter sequence adaptersequence adapter An artificial oligonucleotide of known sequence that can be attached to the 3' or 5' end of a nucleic acid fragment: NOTE: It provides primer sites and other necessary sequences required for sequencing insert fragments: 3:2 Algorithm A fully deterministic finite sequence of instructions by which the value of an output variable can be calculated from the value of an input variable: [Source: IEC 60050-351:2013,351-42-27, with modifications] 3:3 base calling A computational process that converts raw electrical signals from massively parallel sequencing into nucleotide sequences: NOTE: Base calling applications and algorithm performance are determined by read sequence and consensus sequence accuracy: 3:4 The integration and sequential execution of a program, script, or software in which raw data or the output of one program is used as the next input for each step: Example: The output of a base quality shearing program can be used as input to a de novo assembly program: 3:5 captureefficiency The measured target region sequence as a percentage of all sequenced sequences or reference sequences: 3:6 coverage coverage coveragedepth coveragedepth In a sequencing run, the number of times each base at a specified position is sequenced:

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