A Practical Guide to Visualization and Statistical Analysis of R. solanacearum Infection Data Using R

被引:33
作者
Schandry, Niklas [1 ]
机构
[1] Univ Tubingen, Dept Gen Genet, Ctr Mol Biol Plants ZMBP, Tubingen, Germany
关键词
Ralstonia solanacearum; data analysis; linear mixed effects model; survival analysis; regression analysis; non-parametric testing; phytopathology; code: R; RALSTONIA-SOLANACEARUM; PATHOGENIC BACTERIA; CONTRIBUTES; RESISTANCE; COLONIZATION; VIRULENCE; DISEASE; PROTEIN; GENES;
D O I
10.3389/fpls.2017.00623
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
This paper describes and summarizes approaches for visualization and statistical analysis using data from Ralstonia solanacearum infection experiments based on methods and concepts that are broadly applicable. Members of the R. solanacearum species complex cause bacterial wilt disease. Bacterial wilt is a lethal plant disease and has been studied for over 100 years. During this time various methods to quantify disease and different ways to analyze the generated data have been employed. Here, I aim to provide a general background on three distinct and commonly used measures of disease: the area under the disease progression curve, longitudinal recordings of disease severity and host survival. I will discuss how one can proceed with visualization, statistical analysis, and interpretation using different datasets while revisiting the general concepts of statistical analysis. Datasets and R code to perform all analyses discussed here are included in the supplement.
引用
收藏
页数:14
相关论文
共 55 条
[1]   In planta comparative transcriptomics of host-adapted strains of Ralstonia solanacearum [J].
Ailloud, Florent ;
Lowe, Tiffany M. ;
Robene, Isabelle ;
Cruveiller, Stephane ;
Allen, Caitilyn ;
Prior, Philippe .
PEERJ, 2016, 4
[2]  
Allaire J.J., 2015, rmarkdown: Dynamic Documents for R
[3]  
Altman DG, 1998, BRIT MED J, V317, P468
[4]  
[Anonymous], 2016, TIDYVERSE EASILY INS
[5]   Infection processes of xylem-colonizing pathogenic bacteria: possible explanations for the scarcity of qualitative disease resistance genes against them in crops [J].
Bae, Chungyun ;
Han, Sang Wook ;
Song, Yu-Rim ;
Kim, Bo-Young ;
Lee, Hyung-Jin ;
Lee, Je-Min ;
Yeam, Inhwa ;
Heu, Sunggi ;
Oh, Chang-Sik .
THEORETICAL AND APPLIED GENETICS, 2015, 128 (07) :1219-1229
[6]   Fitting Linear Mixed-Effects Models Using lme4 [J].
Bates, Douglas ;
Maechler, Martin ;
Bolker, Benjamin M. ;
Walker, Steven C. .
JOURNAL OF STATISTICAL SOFTWARE, 2015, 67 (01) :1-48
[7]   Natural diversity in the model legume Medicago truncatula allows identifying distinct genetic mechanisms conferring partial resistance to Verticillium wilt [J].
Ben, Cecile ;
Toueni, Maoulida ;
Montanari, Sara ;
Tardin, Marie-Claire ;
Fervel, Magalie ;
Negahi, Azam ;
Saint-Pierre, Laure ;
Mathieu, Guillaume ;
Gras, Marie-Christine ;
Noel, Dominique ;
Prosperi, Jean-Marie ;
Pilet-Nayel, Marie-Laure ;
Baranger, Alain ;
Huguet, Thierry ;
Julier, Bernadette ;
Rickauer, Martina ;
Gentzbittel, Laurent .
JOURNAL OF EXPERIMENTAL BOTANY, 2013, 64 (01) :317-332
[8]   Statistics notes - Survival probabilities (the Kaplan-Meier method) [J].
Bland, JM ;
Altman, DG .
BRITISH MEDICAL JOURNAL, 1998, 317 (7172) :1572-1572
[9]   The logrank test [J].
Bland, JM ;
Altman, DG .
BRITISH MEDICAL JOURNAL, 2004, 328 (7447) :1073-1073
[10]  
Champely S., 2020, PWR BASIC FUNCTIONS