Summary We compared two of the most common methods for differential expression analysis in the RNA-seq field: edgeR and DESeq2. We evaluated these methods based on four real RNA-seq plant datasets. The results indicate that there is a large number of joint differentially expressed genes between the two methods. However, depending on the research goal and the preparation of an experiment, different approaches to statistical analysis and interpretation of the results can be suggested. We focus on answering the question: what workflow should be used in the statistical analysis of the datasets under consideration to minimize the number of falsely identified differentially expressed genes?

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The popularity of hemp cultivation for industrial purposes has been steadily growing for many years. With the addition of products derived from these plants to the Novel Food Catalogue, maintained by the European Commission, a significant increase in interest in hemp food is also expected. The aim of the study was to determine the characteristics of hempseed, oil, and oil cake samples produced from experimental plots grown in different conditions. The research was conducted on the Henola variety, one of the newest and most popular varieties of hemp, recently bred for grain and oil. The content of bioactive compounds in grain and oil has been subjected to detailed chemical analyses in order to determine the effect of fertilization, the method of plant cultivation, and processing conditions on their quantity. The test results and the statistical analysis carried out showed a significant impact of the tested factors on the content of some of the tested bioactive compounds. The obtained results will help in the development of an effective method of cultivation for this hemp variety in order to maximize the content of the desired bioactive compounds per unit of cultivation area.