RNA sequencing analysis is the work of reading which genes are active in a cell, and comparing how active they are between samples. It is also called RNA-seq analysis or gene expression analysis. Some services now hand the results to an AI assistant, which helps the scientist ask questions and understand the answers.
Here is the idea. Every cell in the body carries the same genes, in its DNA. But each cell switches on only some of them. When a gene is switched on, the cell makes copies of it in a molecule called RNA. So by counting the RNA copies of each gene, a scientist can measure how active that gene is. This measure is called gene expression. Reading DNA and RNA is explained in genomics.
The process has four stages. First, a laboratory extracts the RNA from each sample. Second, a DNA sequencer reads millions of short pieces of it. Third, software matches each piece to the gene it came from, and counts the pieces for every gene. Fourth, statistics compare the counts between groups of samples, and list the genes whose activity changed.
Take, for example, a university laboratory in Kolkata that is testing a new compound on liver cancer cells. It grows 12 dishes of cells. It treats 6 dishes with the compound and leaves 6 untreated. The sequencer reads about 25 million pieces of RNA from each dish. The software counts the pieces for each of about 20,000 genes. The statistics find 312 genes that are at least twice as active in the treated cells, and 198 genes that are at least half as active. The scientist then asks the AI assistant, in plain words, "What do the changed genes have in common?" The assistant groups them. It reports that many of the switched-off genes help cells divide. That suggests the compound slows the cancer cells' growth. The scientist checks the statistics and the gene lists herself before she believes the explanation.
That last step matters. An AI assistant can write analysis code quickly, and it can explain results in plain language. But it can also be wrong with confidence, a problem described in AI hallucination. The scientist remains responsible for the conclusion.
RNA sequencing analysis is one part of a bioinformatics data platform. Its results can point a discovery team to a new target protein, as described in computational drug discovery.
How is this different from reading DNA? DNA sequencing shows which genes a cell has, and whether any are faulty. RNA sequencing shows which of those genes the cell is actually using at that moment. So it changes when a cell is treated, sick or stressed.