IntroductionPhred

Base calling projectProblems and outlook

Universtity of Auckland - Bioinformatics InstituteBase calling project

Gabriele Härtinger

Supervisors: David Bryant, Jari Kaipio

10/12/09

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Guide

IntroductionPCRSanger method

PhredOverviewAlgorithms

Base calling projectNon-negative least-squaresMatlab

Problems and outlook

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

PCRSanger method

PCR

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

PCRSanger method

PCR

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

PCRSanger method

Sanger method

source:http://departments.oxy.edu/biology/Stillman/bi221/092200/lecture_notes.htm

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

PCRSanger method

Sanger method

source: http://dnasequencing.wordpress.com/

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

PCRSanger method

Chromatogram

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred

I standard program for base calling

I reads DNA sequencer trace data

I calls bases

I assigns quality values to the bases

I writes the base calls and quality values to output files

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred

I standard program for base calling

I reads DNA sequencer trace data

I calls bases

I assigns quality values to the bases

I writes the base calls and quality values to output files

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred

I standard program for base calling

I reads DNA sequencer trace data

I calls bases

I assigns quality values to the bases

I writes the base calls and quality values to output files

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred

I standard program for base calling

I reads DNA sequencer trace data

I calls bases

I assigns quality values to the bases

I writes the base calls and quality values to output files

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred

I standard program for base calling

I reads DNA sequencer trace data

I calls bases

I assigns quality values to the bases

I writes the base calls and quality values to output files

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.I Dynamic programming algorithm match the predicted peaks

locations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.I Dynamic programming algorithm match the predicted peaks

locations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.I Dynamic programming algorithm match the predicted peaks

locations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.

I Dynamic programming algorithm match the predicted peakslocations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.I Dynamic programming algorithm match the predicted peaks

locations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

OverviewAlgorithms

Phred - Algorithms

I With simple Fourier methods Phred examine the four basetraces.

I Check the region surrounding each point in the data set inorder to predict a series of evenly spaced predicted locations.

I Examine each trace to find the centers of the actual, orobserved, peaks.

I Control every of the four traces separate, many peaks overlap.I Dynamic programming algorithm match the predicted peaks

locations with the observed peaks.Some peaks will be exclude and some will splitted.

I Unmatched observed peaks will compared with the predictedpeak and if found inserted.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Base calling

project:base calling in another way

Deconvolve the peaks with thenon-negative least-squares method.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Base calling

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Non-negative least-squares

I least-squares

y = A x + e ⇒ e = y − A x

min ||e||2 = min ||y − A x ||2 =1N

N∑k=1

e2k ← minimize

I non-negative least-squares method

minx≥0||e||2 = min

x≥0||y − A x ||2 =

1N

N∑k=1

e2k ← minimize

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Non-negative least-squares

I least-squares

y = A x + e ⇒ e = y − A x

min ||e||2 = min ||y − A x ||2 =1N

N∑k=1

e2k ← minimize

I non-negative least-squares method

minx≥0||e||2 = min

x≥0||y − A x ||2 =

1N

N∑k=1

e2k ← minimize

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Matlab - LS

0 20 40 60 80 100 120−0.2

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Blue: true xGreen: ChromatogramRed: regularized LS

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Non-negative least-squaresMatlab

Matlab - NNLS

0 20 40 60 80 100 120−0.2

0

0.2

0.4

0.6

0.8

1

1.2

Blue: NNLSGreen: ChromatogramRed: regularized LS

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Problem

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Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Outlook

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Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project

IntroductionPhred

Base calling projectProblems and outlook

Acknowledgement

A big THANKS to Allen, David, Jari, Peter

and to all of the Bioinformatics Institute.

Gabriele Härtinger Universtity of Auckland - Bioinformatics Institute Base calling project