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2. Sequencing and Basecalling

Sequencing Kit

The pretrained classifier has been trained using data generated from the SQK-RNA004 kit. This kit offers significantly improved data quality compared to its predecessor, SQK-RNA002. To ensure compatibility and optimal performance:

  • Required Kit: Use the SQK-RNA004 kit for sequencing your newly designed synthetic oligos.
  • Rationale: The superior data quality of SQK-RNA004 is crucial for accurate cap type classification.

Read Depth

To achieve robust and reliable learning outcomes:

  • Minimum Read Count: Acquire at least 4 million reads.
  • Recommendation: More reads generally lead to better model performance. If resources allow, consider generating more than the minimum requirement.

Data Processing

For proper preparation of your sequencing data:

  1. Basecalling: Convert raw signal data to nucleotide sequences.
  2. Alignment: Map the basecalled reads to your reference sequence.

Detailed instructions for these steps can be found in the Preprocessing section of our documentation.

Note: Adhering to these requirements ensures that your new data is consistent with data the pretrained model has been trained on.