Analysis of transcriptomic data typically involves several steps:
Quality control: Ensuring the data meets specific standards for accuracy and reliability. Read alignment: Mapping the RNA-Seq reads to a reference genome or transcriptome. Quantification: Measuring the expression levels of transcripts. Normalization: Adjusting for technical variations to make the data comparable across samples. Differential expression analysis: Identifying transcripts that show significant changes in expression under different conditions. Functional annotation: Inferring the biological functions of differentially expressed genes.
