Rpkm/Fpkm Or Tpm Calculator Tbtools

TPM Calculation Formula:

\[ TPM = \frac{RPKM}{\sum RPKM} \times 10^6 \]

TPM Values:

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1. What Is TPM Calculation?

TPM (Transcripts Per Million) is a normalization method for RNA-seq data that accounts for both gene length and sequencing depth. It provides a more accurate comparison of gene expression across samples than RPKM/FPKM.

2. How Does The Calculator Work?

The calculator uses the TPM formula:

\[ TPM = \frac{RPKM}{\sum RPKM} \times 10^6 \]

Where:

\( RPKM \) — Reads Per Kilobase Million value for a gene
\( \sum RPKM \) — Sum of all RPKM values in the sample
\( 10^6 \) — Scaling factor to get per million transcripts

Explanation: TPM normalizes by the sum of all RPKM values, making the total TPM count equal to 1 million across all genes in the sample.

3. Importance Of TPM Normalization

Details: TPM provides a more biologically meaningful normalization than RPKM/FPKM because it accounts for the relative abundance of transcripts within a sample, allowing for better comparison between samples.

4. Using The Calculator

Tips: Enter RPKM values as comma-separated numbers. The calculator will compute the corresponding TPM values for each input RPKM value.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between TPM and RPKM/FPKM?
A: While both normalize for gene length and sequencing depth, TPM additionally normalizes by the sum of all RPKM values, making the total sum equal to 1 million for better cross-sample comparison.

Q2: When should I use TPM instead of RPKM?
A: TPM is generally preferred for comparing expression levels between different samples, while RPKM is better for comparing different genes within the same sample.

Q3: Can I convert FPKM to TPM using the same formula?
A: Yes, the same formula applies for converting both RPKM and FPKM to TPM since they are calculated similarly.

Q4: What are typical TPM value ranges?
A: TPM values typically range from 0 to hundreds of thousands, with highly expressed genes having higher TPM values.

Q5: Does TPM work for single-cell RNA-seq data?
A: While TPM can be used, specialized normalization methods like SCTransform are often preferred for single-cell data due to its unique characteristics.