更新 tutorial/tutorial.md
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@ -9,7 +9,7 @@ FScanpy is a Python package dedicated to predicting Programmed Ribosomal Framesh
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For the prediction of the entire sequence, FScanpy adopts a sliding window approach to scan the entire sequence and predict the PRF sites. For regional prediction, it is based on the 33-bp and 399-bp sequences in the 0 reading frame around the suspected frameshift site. Initially, the Gradient Boosting model will predict the potential PRF sites within the scanning window. If the predicted probability exceeds the threshold, the BiLSTM-CNN model will predict the PRF sites in the 399bp sequence.Then,VotingClassifier will combine the two models to make the final prediction.
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For PRF detection from BLASTX output, FScanpy identifies potential PRF sites from BLASTX alignment results, acquires the two hits of the same query sequence, and then utilizes frameDist_cutoff, mismatch_cutoff, and evalue_cutoff to filter the hits. Finally, it employs [FScanR](https://github.com/seanchen607/FScanR.git) to identify the PRF sites.
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For PRF detection from BLASTX output, [FScanR](https://github.com/seanchen607/FScanR.git) identifies potential PRF sites from BLASTX alignment results, acquires the two hits of the same query sequence, and then utilizes frameDist_cutoff, mismatch_cutoff, and evalue_cutoff to filter the hits. Finally, FScanpy is utilized to predict the probability of PRF sites.
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### Background
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[Ribosomal frameshifting](https://en.wikipedia.org/wiki/Ribosomal_frameshift), also known as translational frameshifting or translational recoding, is a biological phenomenon that occurs during translation that results in the production of multiple, unique proteins from a single mRNA. The process can be programmed by the nucleotide sequence of the mRNA and is sometimes affected by the secondary, 3-dimensional mRNA structure. It has been described mainly in viruses (especially retroviruses), retrotransposons and bacterial insertion elements, and also in some cellular genes.
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