Clustering of RNA-seq Reads by Gene Expression Levels

Sequencing technologies produce a high amount of bioinformatic data. These data are then processed by various algorithms, gathering the information about the DNA structure, the cell condition and many others. In this thesis, we introduce the basic concepts and methods used to process the sequenced data. Specifically, we focus on the gene expression analysis. Standard approaches are based on aligning the input sequences to the reference. Unlike these reference-based pipelines, our main goal is to categorize the input sequences according to the membership to the different genes without any reference. Finally, we compare our solution to the reference-based algorithm.