Phrap and Phred

A Chromatogram showing the sequencing output.

Why Phred ?

• The output of sequencing contains errors
• Because of anomalous migration of very short fragments and unreacted dye-primer or dye-terminator molecules, the first 50 or so peaks of a trace are noisy and unevenly spaced.
• Toward the end of the trace, the peaks become progressively less evenly spaced as a result of less accurate trace processing.
• In better resolved regions of the trace, the most commonly seen electrophoretic anomalies are compressions. These are visible as a peak shifted left of its expected position.
• Weak or variable signal strength and noise peaks not corresponding to a base.

What Phred does ?

• The phred base-caller uses a four-phase procedure to determine a sequence of base-calls from the processed trace.
• In the first phase, idealized peak locations (predicted peaks) are determined. This is done on the basis of the even placement of peaks in most regions of the gel.
• The peak prediction attempts to find the idealized location of the base peaks,using simple fourier methods.
• In the second phase the observed peaks are identified in the trace.
• In the third phase observed peaks are matched to the predicted peak locations, omitting some peaks and and splitting others.
• In the final phase, the uncalled observed peaks are checked for any any peak that appears to represent a base but could not be assigned to a predicted peak in the third phase.
• The calling in this phase is done by means of a criterion that checks
  • If the peak has the largest signal.
  • meets a minimum size criterion
  • is unsplit
  • is flanked by resolved peaks and
  • adding the peak improved peak spacing.
• Returns a quality value = -10 * log_10(P_e)
• Is designed to give output to Phrap.
• Check more on Phred at Base-Calling of Automated Sequencer Traces Using Phred. I. Accuracy Assessment Genome Res. 1998 8: 175-185. and Base-Calling of Automated Sequencer Traces Using Phred. II. Error Probabilities
  Genome Res. 1998 8: 186-194.

Phrap's Algorithm

1. Find pairs of reads with matching words. Eliminate exact duplicate reads. Do swat comparisons of pairs of reads which have matching words, compute (complexity-adjusted) swat score.
2. Find probable vector matches and mark so they aren't used in assembly.
3. Find near duplicate reads.
4. Find reads with self-matches.
5. Find matching read pairs that are "node-rejected" i.e. do not have "solid" matching segments.
6. Use pairwise matches to identify confirmed parts of reads; use these to compute revised quality values.
7. Compute LLR scores for each match (based on qualities of discrepant and matching bases).).(Iterate above two steps).
8. Find best alignment for each matching pair of reads that have more than one significant alignment in a given region (highest LLR-scores among several overlapping).
9. Identify probable chimeric and deletion reads (the latter are withheld from assembly).
10. Construct contig layouts, using consistent pairwise matches in decreasing score order (greedy algorithm). Consistency of layout is checked at pairwise comparison level.
11. Construct contig sequence as a mosaic of the highest quality parts of the reads.Align reads to contig; tabulate inconsistencies (read / contig discrepancies) & possible sites of misassembly. Adjust LLR-scores of contig sequence.

Check more on Phrap at Phrap.

Information compiled from linked sources by: Rohan Jude Fernandes