freeCount: A Coding Free Framework for Guided Count Data Visualization and Analysis

被引：0
|
作者：
Brooks, Elizabeth M. [1 ]
Sanders, Sheri A. [1 ]
Pfrender, Michael E. [1 ]
机构：
[1] Univ Notre Dame, Notre Dame, IN 46556 USA
来源：
PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING 2024, PEARC 2024 | 2024年
基金：
美国国家科学基金会;
关键词：
R Shiny; Interactive Interfaces; Analysis Framework; Genomics; Transcriptomics; Metagenomics;
D O I：
10.1145/3626203.3670605
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The analysis and interpretation of high-dimensional biological data sets is a challenging task. Exploratory data analysis of count data produced by next-generation sequencing technologies presents a common hurdle to researchers. Biologists often find it difficult to get started with the analysis process, which can be time consuming and repetitive. With the freeCount analysis framework students and researchers are guided through the iterative steps of data assessment, processing, and analysis in a visual environment. The freeCount analysis framework takes advantage of the reactive features of R Shiny to deliver a set of modular and interactive tools and tutorials for the structured analysis and visualization of count data.
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页数：4
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