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Download SAPPHIRE
For sequences longer than 5k basepairs, it is advisable to download SAPPHIRE and run it locally.
Required python3 packages: | numpy, keras, biopython |
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Usage: |
cd to SAPPHIRE directory Run: python3 *SAPPHIRE version*.py input.fasta Or (to include the reverse complements): python3 *SAPPHIRE version*.py -r input.fasta |
Available SAPPHIRE versions: |
SAPPHIRE.py SAPPHIRE_CNN_pseudomonas.py SAPPHIRE_CNN_salmonella.py |
References
SAPPHIRE
Coppens, L., & Lavigne, R. (2020). SAPPHIRE: a neural network based classifier for σ70 promoter prediction in Pseudomonas. In BMC Bioinformatics (Vol. 21, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s12859-020-03730-z
SAPPHIRE.CNN
Coppens, L., Wicke, L., & Lavigne, R. (2022). SAPPHIRE.CNN: Implementation of dRNA-seq-driven, species-specific promoter prediction using convolutional neural networks. In Computational and Structural Biotechnology Journal (Vol. 20, pp. 4969–4974). Elsevier BV. https://doi.org/10.1016/j.csbj.2022.09.006