TimelyScholarFree Tools › Log2 Fold Change Calculator
Calculate log2 fold changes between treatment and control samples for every gene in a table, from log-scale or linear values, and download the ranked results.
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| Gene | Mean control | Mean treatment | log2 fold change | Fold change |
|---|---|---|---|---|
| Gene08 | 9.557 | 6.977 | -2.580 | 0.167 |
| Gene01 | 9.437 | 11.697 | 2.260 | 4.790 |
| Gene10 | 7.273 | 5.213 | -2.060 | 0.240 |
| Gene06 | 10.830 | 12.847 | 2.017 | 4.046 |
| Gene07 | 9.147 | 7.207 | -1.940 | 0.261 |
| Gene05 | 4.537 | 6.230 | 1.693 | 3.234 |
| Gene03 | 10.123 | 11.757 | 1.633 | 3.102 |
| Gene02 | 7.083 | 8.667 | 1.583 | 2.997 |
| Gene09 | 4.770 | 3.277 | -1.493 | 0.355 |
| Gene11 | 6.157 | 4.683 | -1.473 | 0.360 |
| Gene04 | 8.717 | 10.180 | 1.463 | 2.757 |
| Gene18 | 5.120 | 4.130 | -0.990 | 0.503 |
| Gene21 | 9.643 | 8.997 | -0.647 | 0.639 |
| Gene24 | 9.977 | 10.440 | 0.463 | 1.379 |
| Gene14 | 9.533 | 9.977 | 0.443 | 1.360 |
| Gene12 | 10.683 | 10.243 | -0.440 | 0.737 |
| Gene15 | 6.980 | 7.387 | 0.407 | 1.326 |
| Gene16 | 5.663 | 5.363 | -0.300 | 0.812 |
| Gene13 | 8.363 | 8.517 | 0.153 | 1.112 |
| Gene19 | 9.683 | 9.830 | 0.147 | 1.107 |
| Gene20 | 8.303 | 8.163 | -0.140 | 0.908 |
| Gene17 | 7.767 | 7.630 | -0.137 | 0.910 |
| Gene23 | 10.817 | 10.720 | -0.097 | 0.935 |
| Gene22 | 6.550 | 6.587 | 0.037 | 1.026 |
For log2 data, log2 fold change = mean(treatment) − mean(control). This is a descriptive calculation. For RNA-seq counts, use a statistical method such as DESeq2, which models count variability and shrinks noisy fold changes.
Genes in rows, samples in columns.
The remaining samples are controls.
Ranked by the size of the change.
Fold change is the ratio of expression between two conditions. Taking log2 makes increases and decreases symmetric: +1 is a doubling, −1 is a halving and 0 is no change.
This calculator gives descriptive fold changes. For RNA-seq counts, statistical methods such as DESeq2 estimate fold changes while accounting for count variability and shrink unreliable estimates from low-count genes.
Expression is 2^1.5 ≈ 2.8 times higher in the treatment group.