2篇
您的检索式：作者名="Tongwu Zhang"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | BIGpre: A Quality Assessment Package for Next-Generation Sequencing Data显示文摘The emergence of next-generation sequencing (NGS) technologies has significantly improved sequencing throughput and reduced costs. However, the short read length, duplicate reads and massive volume of data make the data processing much more difficult and complicated than the first-generation sequencing technology. Although there are some software packages developed to assess the data quality, those packages either are not easily available to users or require bioinformatics skills and computer resources. Moreover, almost all the quality assessment software currently available didn't taken into account the sequencing errors when dealing with the duplicate assessment in NGS data. Here, we present a new user-friendly quality assessment software package called BIGpre, which works for both Illumina and 454 platforms. BIGpre contains all the functions of other quality assessment software, such as the correlation between forward and reverse reads, read GC-content distribution, and base Ns quality. More importantly, BIGpre incorporates associated programs to detect and remove duplicate reads after taking sequencing errors into account and trimming low quality reads from raw data as well. BIGpre is primarily written in Perl and integrates graphical capability from the statistics package R. This package produces both tabular and graphical summaries of data quality for sequencing datasets from Illumina and 454 platforms. Processing hundreds of millions reads within minutes, this package provides immediate diagnostic information for user to manipulate sequencing data for downstream analyses. BIGpre is freely available at http://bigpre.sourceforge.net/. | Tongwu Zhang Yingfeng Luo Kan Liu Linlin Pan Bing Zhang Jun Yu Songnlan Hu | 2011 | Genomics, Proteomics & Bioinformatics2011，9，6： | 3 |
| 2 | ezQTL:A Web Platform for Interactive Visualization and Colocalization of QTLs and GWAS Loci显示文摘Genome-wide association studies(GWAS)have identified thousands of genomic loci associated with complex diseases and traits,including cancer.The vast majority of common traitassociated variants identified via GWAS fall in non-coding regions of the genome,posing a challenge in elucidating the causal variants,genes,and mechanisms involved.Expression quantitative trait locus(eQTL)and other molecular QTL studies have been valuable resources in identifying candidate causal genes from GWAS loci through statistical colocalization methods.While QTL colocalization is becoming a standard analysis in post-GWAS investigation,an easy web tool for users to perform formal colocalization analyses with either user-provided or public GWAS and eQTL datasets has been lacking.Here,we present ezQTL,a web-based bioinformatic application to interactively visualize and analyze genetic association data such as GWAS loci and molecular QTLs under different linkage disequilibrium(LD)patterns(1000 Genomes Project,UK Biobank,or user-provided data).This application allows users to perform data quality control for variants matched between different datasets,LD visualization,and two-trait colocalization analyses using two state-of-the-art methodologies(eCAVIAR and HyPrColoc),including batch processing.ezQTL is a free and publicly available cross-platform web tool,which can be accessed online at https://analysistools.cancer.gov/ezqtl. | Tongwu Zhang Alyssa Klein Jian Sang Jiyeon Choi Kevin M.Brown | 2022 | Genomics, Proteomics & Bioinformatics2022，20，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员