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A Software Platform for Somatic Variant Calling using Next-generation Sequencing Data

Title
A Software Platform for Somatic Variant Calling using Next-generation Sequencing Data
Translated Title
체세포 변이 탐지를 위한 NGS 데이터 분석 소프트웨어 플랫폼
Authors
Kim, Seon Ho
DGIST Authors
Kim, Seon Ho; Kim, Min Soo; Hwang, Dae Hee
Advisor(s)
Kim, Min Soo
Co-Advisor(s)
Hwang, Dae Hee
Issue Date
2015
Available Date
2015-08-18
Degree Date
2015. 8
Type
Thesis
Keywords
cancer genome analysisNGSsomatic mutation detection암 게놈 분석체세포 변이 탐지
Abstract
Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Accurate detection of somatic mutation is an essential part of cancer genome analysis, and plays an important role in oncotarget identifications. Next generation sequencing (NGS) holds the promise to revolutionize somatic mutation detection. A lot of computational methods are developed for cancer sequencing data processing and analysis. However, few tools are specialized for cancer genome and sample characteristics because most methods initially focus on normal genome sequencing data. Here, we surveyed computational methods for detecting mutations for whole-genome/whole-exome cancer sequencing data analysis supporting four distinct mutation types: single nucleotide variants (SNVs), small insertions or deletions (Indels), copy number variations (CNVs), and large structural variants (SVs). We discuss the problems and challenges of current methods and also present a software platform for somatic variant calling that may improve calling accuracy and computational power. ⓒ 2015 DGIST
Table Of Contents
Ⅰ. INTRODUCTION 1 -- Ⅱ. NGS CANCER GENOME ANALYSIS 3 -- 2.1 NGS studies 3 -- 2.2 Cancer-specific consideration 3 -- 2.3 NGS cancer genome analysis 5 -- 2.4 NGS Cancer genome sequencing data processing 7 -- Ⅲ. SOMATIC VARIANT DETECTION METHODS 9 -- 3.1 Pipeline overview 9 -- 3.2 SNV detection 9 -- 3.3 Small Indel and SV detection 10 -- 3.4 CNVs detection 11 -- Ⅳ. SOFTWARE PLATFORM FOR SOMATIC VARIANT CALLING 14 -- 4.1 Platform overview 14 -- 4.2 Platform architecture 14 -- Ⅴ. CONCLUSIONS 15
URI
http://dgist.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002076295
http://hdl.handle.net/20.500.11750/1406
DOI
10.22677/thesis.2076295
Degree
Master
Department
Information and Communication Engineering
University
DGIST
Files:
Collection:
Information and Communication EngineeringThesesMaster


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