Biology has changed a lot over the past decade, driven by ever-cheaper data gathering technologies: genomics, transcriptomics, proteomics, metabolomics and imaging of all sorts. After a few years of gleeful abandon in the data generation department, analysis has come to the fore, demanding a whole new outlook and on-going collaboration between scientists, statisticians, engineers and others who bring to the table a very broad range of skills and experience.
Continue reading “Advice on Big Data Experiments and Analysis, Part I: Planning”