Analyzing single cell sequencing data involves several steps. Initial processing includes quality control and alignment of sequencing reads. Subsequent steps involve clustering cells based on gene expression profiles and identifying differentially expressed genes. Advanced machine learning algorithms are often employed to handle the complexity and scale of the data, enabling researchers to draw meaningful conclusions about cellular responses to toxic exposures.
