Tridentine wedding mass program: full version software

The goal of the project is to reveal differentially expressed genes (DEGs) of both protein-coding genes (mRNAs) and genes encoding small regulatory RNAs, in particular miRNAs. A time-course analysis of three typical stages of the diseases onset was realised. The data constitutes in data from RNA-seq experiments of resistant or susceptible plants infected or not by a soil pathogen ( Verticillium alfalfae) and of sRNA-Seq data of the same samples. Our model species is Medicago truncatula, a wild species developped as a model species for legumes - the second most important plant family that produces most of proteins for feed and food (soybean, beans, peas, alfalfa) We intend to explore resistance and defense mechanisms against Verticillium wilt, a major soil-borne root pathogen of plants, and more generally to gain knowledge on the molecular mechanisms involved in Quantitative Disease Resistance in plants. Although in most cases these attacks are efficiently encountered by the plants' natural defense mechanisms, plant disease is still a major constraint in agricultural productivity. Plants continuously have to cope with attacks from pathogens or pests. They will be working alongside skilful bioinformaticians and their results will be impactful both for the company and scientific community worldwide.

Students will have access to high-performance computing servers to analyse big single-cell data. In the end they will contribute to the development of the golden standard for single-cell data analysis.

They will mine the public databases to collect high-quality single-cell datasets and develop a benchmark to evaluate the efficacy, time and memory requirements of popular tools. Successful students will study the most popular tools for data integration, including ComBat, Harmony, MNN and others. The single-cell transcriptomics analysis has multiple steps, but we will focus on data integration вЂ“ a crucial step when working with clinical data coming from patients. The goal of this project is to tackle the complexity of data analysis by identifying the best approaches. However, the analysis of single-cell data is incredibly complex with numerous distinct approaches resulting in more than 500 Python and R libraries existing today. It is the next step towards making precision medicine more accurate.

Single-cell sequencing is paving the way for precision medicine.

Tridentine wedding mass program: full version software