scholarly journals RETA: An R package for whole exome and targeted region sequencing data analysis

2017 ◽  
Author(s):  
Mengbiao Guo ◽  
Jing Yang ◽  
Yu lung Lau ◽  
Wanling Yang
Keyword(s):  
Data Analysis ◽  
R Package ◽  
Targeted Sequencing ◽  
Sequencing Data ◽  
Comprehensive Understanding ◽  
Mendelian Diseases ◽  
Whole Exome ◽  
One Stop ◽  
Sequencing Data Analysis ◽  
Advanced Visualization

AbstractWhole exome and targeted sequencing have been playing a major role in diagnoses of Mendelian diseases, but analysis of these data involves using many complicated tools and comprehensive understanding of the analysis results is difficult.Here, we report RETA, an R package to provide a one-stop analysis of these data and a comprehensive, interactive and easy-to-understand report with many advanced visualization features. It facilitates clinicians and scientists alike to better analyze and interpret this type of sequencing data for disease diagnoses.Availability and implementationhttps://github.com/reta-s/reta/[email protected]

scholarly journals Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Genomics ◽  
2017 ◽  
Vol 109 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Yan Guo ◽  
Yulin Dai ◽  
Hui Yu ◽  
Shilin Zhao ◽  
David C. Samuels ◽  
...  
Keyword(s):  
Data Analysis ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Sequencing Data Analysis

scholarly journals hypeR: An R Package for Geneset Enrichment Workflows

2019 ◽  
Author(s):  
Anthony Federico ◽  
Stefano Monti
Keyword(s):  
High Throughput Sequencing ◽  
R Package ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Wide Audience ◽  
Popular Method ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
One Stop ◽  
Recent Version

ABSTRACTSummaryGeneset enrichment is a popular method for annotating high-throughput sequencing data. Existing tools fall short in providing the flexibility to tackle the varied challenges researchers face in such analyses, particularly when analyzing many signatures across multiple experiments. We present a comprehensive R package for geneset enrichment workflows that offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting. hypeR is a one-stop solution to performing geneset enrichment for a wide audience and range of use cases.Availability and implementationThe most recent version of the package is available at https://github.com/montilab/hypeR.Supplementary informationComprehensive documentation and tutorials, are available at https://montilab.github.io/hypeR-docs.

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis

2017 ◽  
Vol 20 (1) ◽  
pp. 222-234 ◽  
Author(s):  
Saira Afzal ◽  
Irene Gil-Farina ◽  
Richard Gabriel ◽  
Shahzad Ahmad ◽  
Christof von Kalle ◽  
...  
Keyword(s):  
Data Analysis ◽  
T Cell ◽  
Comparative Study ◽  
T Cell Receptor ◽  
Computational Methods ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Sequencing Data Analysis
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