We are analyzing https://link.springer.com/article/10.1007/s12064-012-0162-3.

Title:
Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples | Theory in Biosciences
Description:
Measures of RNA abundance are important for many areas of biology and often obtained from high-throughput RNA sequencing methods such as Illumina sequence data. These measures need to be normalized to remove technical biases inherent in the sequencing approach, most notably the length of the RNA species and the sequencing depth of a sample. These biases are corrected in the widely used reads per kilobase per million reads (RPKM) measure. Here, we argue that the intended meaning of RPKM is a measure of relative molar RNA concentration (rmc) and show that for each set of transcripts the average rmc is a constant, namely the inverse of the number of transcripts mapped. Further, we show that RPKM does not respect this invariance property and thus cannot be an accurate measure of rmc. We propose a slight modification of RPKM that eliminates this inconsistency and call it TPM for transcripts per million. TPM respects the average invariance and eliminates statistical biases inherent in the RPKM measure.
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Keywords {🔍}

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Topics {✒️}

month download article/chapter koryu kin & vincent rna sequencing isoform expression rna-seq data privacy choices/manage cookies full article pdf gene 344 author correspondence european economic area quantifying mammalian transcriptomes lawrence erlbaum associates derived digit identities illumina sequence data conditions privacy policy sequencing approach sequencing depth rna-seq electronic supplementary material check access instant access rna abundance rna species accepting optional cookies transcriptomics main content log article theory journal finder publish article log nat methods 5 related subjects article cite article wagner personal data privacy policy books a supplementary material 1 kin optional cookies manage preferences statistical inferences yale university theory biosci data protection subscription content rpkm measure rev biol 86 essential cookies cookies skip biosciences aims

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         description:Measures of RNA abundance are important for many areas of biology and often obtained from high-throughput RNA sequencing methods such as Illumina sequence data. These measures need to be normalized to remove technical biases inherent in the sequencing approach, most notably the length of the RNA species and the sequencing depth of a sample. These biases are corrected in the widely used reads per kilobase per million reads (RPKM) measure. Here, we argue that the intended meaning of RPKM is a measure of relative molar RNA concentration (rmc) and show that for each set of transcripts the average rmc is a constant, namely the inverse of the number of transcripts mapped. Further, we show that RPKM does not respect this invariance property and thus cannot be an accurate measure of rmc. We propose a slight modification of RPKM that eliminates this inconsistency and call it TPM for transcripts per million. TPM respects the average invariance and eliminates statistical biases inherent in the RPKM measure.
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            Bioinformatics
            Philosophy of Biology
            Theoretical Ecology/Statistics
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      headline:Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples
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