Rpkm Fpkm Or Tpm Calculator Tbtools

TPM Formula:

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

TPM Values:

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1. What is TPM?

TPM (Transcripts Per Million) is a normalized unit for RNA-seq gene expression quantification. It accounts for both gene length and sequencing depth, providing 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 gene expression by the total expression in the sample, making it easier to compare expression levels between genes within the same sample.

3. Importance of TPM Calculation

Details: TPM provides a more biologically meaningful measure of transcript abundance than RPKM/FPKM. It's particularly useful when comparing the relative abundance of transcripts within a sample or when performing downstream analyses like differential expression.

4. Using the Calculator

Tips: Enter RPKM values separated by commas. The calculator will compute the corresponding TPM values for each input. All values must be valid numbers.

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 total expression in the sample, making the sum of all TPM values equal to 1 million.

Q2: When should I use TPM instead of RPKM?
A: TPM is generally preferred for within-sample comparisons and when you want to know what percentage of transcripts in a cell belong to a particular gene.

Q3: Can I convert FPKM to TPM using the same formula?
A: Yes, the same formula applies since FPKM and RPKM are conceptually similar (FPKM is for paired-end data).

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

Q5: Is TPM suitable for between-sample comparisons?
A: While TPM is better for within-sample comparisons, for between-sample comparisons, additional normalization methods like DESeq2 or edgeR are often recommended.