| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 2825817 | Trends in Plant Science | 2014 | 4 Pages |
•Statistical data analysis skills are important for plant research.•Key concepts and common problems of data analysis are discussed.•RNAseq analysis is used as a case study to illustrate data analysis concepts.•We recommend free online resources for gaining data analysis skills.
Plant biology is becoming a data-driven science. High-throughput technologies generate data quickly from molecular to ecosystem levels. Statistical and computational approaches enable describing and interpreting data quantitatively. We highlight the purpose, common problems, and general principles in data analysis. We use RNA sequencing (RNAseq) analysis to illustrate the rationale behind some of the choices made in statistical data analysis. Finally, we provide a list of free online resources that emphasize intuition behind quantitative data analysis.
