RPKMFPKM

RPKMFPKM is not a standard metric in public literature. The term may appear as a shorthand error or informal reference to either RPKM or FPKM, or to a dataset labeled with both. A wiki-style article on this topic typically clarifies the two established measures and discusses how they relate, rather than introducing a distinct, widely accepted formula.

RPKM stands for Reads Per Kilobase of transcript per Million mapped reads. It normalizes the count of reads C aligning to a gene by the gene length L (in base pairs) and the total number of mapped reads N. The formula is RPKM = (C × 10^9) / (N × L).

FPKM stands for Fragments Per Kilobase of transcript per Million mapped fragments. It is used for paired-end RNA-Seq where a fragment may generate two reads; it uses the number of fragments F instead of reads. The formula is FPKM = (F × 10^9) / (N × L).

Differences and use: RPKM uses reads and is typical for single-end data; FPKM uses fragments and is more appropriate for paired-end data. In practice, values are often similar for comparable data, but the definitions differ in what counts as a counted molecule.

Comparison across samples: Neither RPKM nor FPKM is directly comparable across samples without careful normalization; TPM (Transcripts Per Million) is often preferred for cross-sample comparisons because it normalizes for gene length and sequencing depth in a way that yields sum-to-one across transcripts within each sample.

Current status: Since the 2010s, both metrics have been largely superseded by TPM and by count-based methods for differential expression analysis (e.g., DESeq2, edgeR). When reporting expression levels, researchers may present both RPKM/FPKM values and note the normalization method used, or prefer TPM for cross-sample comparisons.