code: def phred_sequences_to_probability(phred_qualities):
      """Converts raw phred quality scores into base-calling error probabilities.
  
      For each ASCII encoded phred quality score (X), the probability that there
      was an error calling that base is computed by:
  
      P = 10 ^ (-(X - 33) / 10)
  
      This is assuming an "ASCII base" of 33.
  
      The input is a tf.string tensor of ASCII encoded phred qualities,
      one string per DNA sequence, with each character representing the quality
      of a nucelotide.
  
      For example:
      phred_qualities = [["BB<"], ["BBBB"]]
  
      Args:
          phred_qualities: A tf.string tensor where each string represents the phred
                          quality of a DNA sequence. Each character in the string
                          is the ASCII representation of the phred quality number.
  
      Returns:
          tf.RaggedTensor: The quality scores for each base in each sequence provided.
      """
      return tf.ragged.map_flat_values(
          _phred_sequence_to_probability,
          tf.strings.bytes_split(phred_qualities),
      )
  
file_path: io/tensorflow_io/python/ops/genome_ops.py
imports: import tensorflow
  from tensorflow_io.python.ops import core_ops
label_desc: Use image node_id 7 for calling a global function with example usage: phred_sequences_to_probability(phred_qualities) and returns: tf