An overview of tools for post-analysis of high-throughput sequencing data in clinical study.
10.3760/cma.j.issn.1003-9406.2019.05.024
- Author:
Yali HAN
1
;
Zaiwei ZHOU
1
;
Jingzhi ZHANG
2
,
3
Author Information
1. Shanghai Institute of Medical Genetics, Children's Hospital of Shanghai, Children's Hospital Affiliated to Shanghai Jiao Tong University, Shanghai 200040, China.
2. Shanghai Institute of Medical Genetics, Children's Hospital of Shanghai, Children's Hospital Affiliated to Shanghai Jiao Tong University, Shanghai 200040, China
3. Key Laboratory of Embryo Molecular Biology, Ministry of Health, Shanghai Key Laboratory of Embryo and Reproduction Engineering, Shanghai 200040, China. Email: jzhang38@hotmail.com.
- Publication Type:Journal Article
- MeSH:
Genetic Association Studies;
High-Throughput Nucleotide Sequencing;
Humans;
Phenotype;
Sequence Analysis, DNA;
Software
- From:
Chinese Journal of Medical Genetics
2019;36(5):508-512
- CountryChina
- Language:Chinese
-
Abstract:
With the advance of high-throughout sequencing technology and its extensive application in clinical diagnosis, analysis of sequencing data has become an important part of clinical diagnosis. To date, the development and establishment of various software and databases have made it convenient to extract useful information from massive amounts of high-throughput sequencing data. However, it is still a challenge for correlating the clinical-genetic diagnosis based on the above-mentioned sequence data with the screened DNA variations and disease phenotypes. Further validation of the proposed pathogenesis with the discovered molecular defects are required. Here a comprehensive review is provided for the strategies of sequencing data analysis, commonly used phenotype-genotype correlation tools, and functional analysis and verification methods for the genetic diagnosis.
