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.
引用
收藏
页数：4
相关论文
共 50 条
  • [41] The gameplay visualization manifesto: A framework for logging and visualization of online gameplay data
    Joslin, Simon
    Brown, Ross
    Drennan, Penny
    Computers in Entertainment, 2007, 5 (03):
  • [42] A Data Driven Framework to Teach Visualization Design
    Panda, Swaroop
    Roy, Shatarupa Thakurta
    PROCEEDINGS OF THE 12TH INDIAN CONFERENCE ON HUMAN-COMPUTER INTERACTION, INDIA HCI 2021, 2021, : 145 - 147
  • [43] VISAGE - A VISUALIZATION AND EXPLORATION FRAMEWORK FOR ENVIRONMENTAL DATA
    Conover, Helen
    Berendes, Todd
    Gatlin, Patrick
    Maskey, Manil
    Naeger, Aaron
    Wingo, Stephanie
    Kulkarni, Ajinkya
    Marouane, Abdelhak
    Wang, Lihua
    Ellingson, Brian
    Dahal, Bibek
    Singhirunnusorn, Khomsun
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 5405 - 5408
  • [44] DEEPEYE: An Automatic Big Data Visualization Framework
    Xuedi Qin
    Yuyu Luo
    Nan Tang
    Guoliang Li
    Big Data Mining and Analytics, 2018, (01) : 75 - 82
  • [45] A framework for data visualization based on particle systems
    Birra, FP
    dos Santos, MP
    WSCG '98, VOL 1: SIXTH INTERNATIONAL CONFERENCE IN CENTRAL EUROPE ON COMPUTER GRAPHICS AND VISUALIZATION '98, 1998, : 41 - 48
  • [46] An interactive parallel visualization framework for distributed data
    Perrine, KA
    Jones, DR
    Hochschild, P
    Swetz, RA
    VISUALIZATION AND DATA ANALYSIS 2002, 2002, 4665 : 196 - 206
  • [47] DEEPEYE: An Automatic Big Data Visualization Framework
    Qin, Xuedi
    Luo, Yuyu
    Tang, Nan
    Li, Guoliang
    BIG DATA MINING AND ANALYTICS, 2018, 1 (01): : 75 - 82
  • [48] A Unified Framework for Neuroscience Morphological Data Visualization
    Pastor, Luis
    Bayona, Sofia
    Brito, Juan P.
    Cuevas, Maria
    Fernaud, Isabel
    Emilio Galindo, Sergio
    Jose Garcia-Cantero, Juan
    Gonzalez de Quevedo, Francisco
    Mata, Susana
    David Robles, Oscar
    Rodriguez, Angel
    Toharia, Pablo
    Zdravkovic, Ana
    APPLIED SCIENCES-BASEL, 2021, 11 (10):
  • [49] VizLinter: A Linter and Fixer Framework for Data Visualization
    Chen, Qing
    Sun, Fuling
    Xu, Xinyue
    Chen, Zui
    Wang, Jiazhe
    Cao, Nan
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2022, 28 (01) : 206 - 216
  • [50] Data stream visualization framework for smart cities
    Villanueva, F. J.
    Aguirre, C.
    Rubio, A.
    Villa, D.
    Santofimia, M. J.
    Lopez, J. C.
    SOFT COMPUTING, 2016, 20 (05) : 1671 - 1681
12345