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The tricky art of scaling quantitative data across libraries, typically to account for differences in sequencing depth. This can also be about scaling for read source length, like transcript or gene length, in order to enable comparisons across genes.
8
votes
Confirm success or failure of RNA-Seq normalization
Prior to normalization, your abundances may look something like this.
Post-normalization, they should look something like this.
See this blog post for example code. …
9
votes
Accepted
How to read and interpret a gene expression quantification file?
The first column contains Ensembl gene identifiers, and the suffix is a version number that can be used to track changes to the gene annotations over time. From the Ensembl Stable IDs documentation:
…