Literature DB >> 30416327

Interactive Visualization of Hierarchically Structured Data.

Kris Sankaran1, Susan Holmes2.   

Abstract

We introduce methods for visualization of data structured along trees, especially hierarchically structured collections of time series. To this end, we identify questions that often emerge when working with hierarchical data and provide an R package to simplify their investigation. Our key contribution is the adaptation of the visualization principles of focus-plus-context and linking to the study of tree-structured data. Our motivating application is to the analysis of bacterial time series, where an evolutionary tree relating bacteria is available a priori. However, we have identified common problem types where, if a tree is not directly available, it can be constructed from data and then studied using our techniques. We perform detailed case studies to describe the alternative use cases, interpretations, and utility of the proposed visualization methods.

Entities:  

Keywords:  D3; R; focus-plus-context; linking; time-series; tree-structured

Year:  2017        PMID: 30416327      PMCID: PMC6223648          DOI: 10.1080/10618600.2017.1392866

Source DB:  PubMed          Journal:  J Comput Graph Stat        ISSN: 1061-8600            Impact factor:   2.302


  12 in total

1.  Extracting regression rules from neural networks.

Authors:  Kazumi Saito; Ryohei Nakano
Journal:  Neural Netw       Date:  2002-12

2.  Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

Authors:  J Gregory Caporaso; Christian L Lauber; William A Walters; Donna Berg-Lyons; Catherine A Lozupone; Peter J Turnbaugh; Noah Fierer; Rob Knight
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-03       Impact factor: 11.205

3.  structSSI: Simultaneous and Selective Inference for Grouped or Hierarchically Structured Data.

Authors:  Kris Sankaran; Susan Holmes
Journal:  J Stat Softw       Date:  2014-09-12       Impact factor: 6.440

Review 4.  The human microbiome: at the interface of health and disease.

Authors:  Ilseung Cho; Martin J Blaser
Journal:  Nat Rev Genet       Date:  2012-03-13       Impact factor: 53.242

5.  Structure, function and diversity of the healthy human microbiome.

Authors: 
Journal:  Nature       Date:  2012-06-13       Impact factor: 49.962

6.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

7.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Authors:  Michael I Love; Wolfgang Huber; Simon Anders
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

8.  phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Authors:  Paul J McMurdie; Susan Holmes
Journal:  PLoS One       Date:  2013-04-22       Impact factor: 3.240

9.  The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing.

Authors:  Les Dethlefsen; Sue Huse; Mitchell L Sogin; David A Relman
Journal:  PLoS Biol       Date:  2008-11-18       Impact factor: 8.029

10.  Bioconductor workflow for microbiome data analysis: from raw reads to community analyses.

Authors:  Ben J Callahan; Kris Sankaran; Julia A Fukuyama; Paul J McMurdie; Susan P Holmes
Journal:  F1000Res       Date:  2016-06-24
View more
  2 in total

Review 1.  Microbiome data science.

Authors:  Sudarshan A Shetty; Leo Lahti
Journal:  J Biosci       Date:  2019-10       Impact factor: 1.826

Review 2.  An Integrated Multi-Disciplinary Perspectivefor Addressing Challenges of the Human Gut Microbiome.

Authors:  Rohan M Shah; Elizabeth J McKenzie; Magda T Rosin; Snehal R Jadhav; Shakuntla V Gondalia; Douglas Rosendale; David J Beale
Journal:  Metabolites       Date:  2020-03-06
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.