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/*
* Copyright (c) Medical Research Council 2002. All rights reserved.
*
* Permission to use, copy, modify and distribute this software and its
* documentation for any purpose is hereby granted without fee, provided that
* this copyright and notice appears in all copies.
*
* This file was written as part of the Staden Package at the MRC Laboratory
* of Molecular Biology, Hills Road, Cambridge, CB2 2QH, United Kingdom.
*
* MRC disclaims all warranties with regard to this software.
*
*/
#include <cassert>
#include <cstring> // For std::strcpy(), std::strcat()
#include <cstdio> // For std::sprintf()
#include <mutscan_preprocess.hpp>
// #define VERBOSE_DEBUG
/**
Master routine that invokes each preprocessing stage in turn.
*/
mutlib_result_t MutScanPreprocessor::Execute( mutscan_t* ms, Trace& t, int n, int left, int right )
{
assert(ms != NULL);
assert(ms->Initialised);
// Get algorithm parameters, we set the adaptive noise threshold for
// the reference to be twice that of the input. This is so we have a
// rock solid reference signal without missing low level peaks on the
// input trace.
PeakInterval = t.IntervalMode();
SearchWindow = ms->Parameter[MUTSCAN_PARAMETER_SEARCH_WINDOW] * PeakInterval;
m_nNoiseThreshold[0] = ms->Parameter[MUTSCAN_PARAMETER_NOISE_THRESHOLD] * 2.0;
m_nNoiseThreshold[1] = ms->Parameter[MUTSCAN_PARAMETER_NOISE_THRESHOLD];
assert(SearchWindow>1.0);
assert(m_nNoiseThreshold[0]!=0.0);
assert(m_nNoiseThreshold[1]!=0.0);
// Start preprocessing
PeakFind( t, left, right );
EstimateNoiseFloor( t, n );
PeakClip();
PeakSpacing();
CountPeaks();
if( PeakCount.Max() < 3 )
{
ms->ResultCode = MUTLIB_RESULT_INSUFFICIENT_DATA;
std::sprintf( ms->ResultString, "Insufficent data to process trace %s.\n", t.Name() );
return MUTLIB_RESULT_INSUFFICIENT_DATA;
}
return MUTLIB_RESULT_SUCCESS;
}
/**
Scans the trace for peaks and records their amplitude and position
in the 4 * SAMPLES Peak matrix.
To avoid discontinuities at the edges, we only search for peaks
within the two margins, left/right. This avoids false positives.
*/
void MutScanPreprocessor::PeakFind( Trace& Tr, int left, int right )
{
int pos;
int resume;
const int rows = 4;
const int cols = Tr.Samples();
// Allocate and initialise the peak matrix
Peak.Create( rows+1, cols );
Peak.Fill( 0 );
// Create a peaks matrix from the trace
for( int r=0; r<rows; r++ )
{
resume = left;
while(1)
{
pos = Tr.PosPeakFind( r, resume, right, resume, 1 );
if( pos > 0 )
Peak[r][pos] = Tr[r][pos];
else
break;
}
}
}
/**
Computes an estimate of the trace noise floor from the envelope
and records it in the 1*SAMPLES Noise vector.
*/
void MutScanPreprocessor::EstimateNoiseFloor( Trace& Tr, int n )
{
int a[2];
int pos;
int resume;
const int rows = 4;
const int cols = Peak.Cols();
// Allocate and initialise noise floor vector
Noise.Create( cols );
Noise.Fill( 0 );
// Create the trace envelope
Trace* pEnvelope = Tr.CreateEnvelope();
Trace& Envelope = *pEnvelope;
// Find all peaks in the envelope
resume = 0;
while(1)
{
pos = Envelope.PosPeakFind( 0, resume, cols-1, resume, 1 );
if( pos >= 0 )
{
// Noise estimate at current position is a fixed percentage of
// the envelope peak height
a[0] = Envelope[0][pos];
a[1] = static_cast<int>( m_nNoiseThreshold[n] * a[0] );
Noise[pos] = a[1];
}
else
break;
}
// Interpolate through non-zero noise points to complete our noise estimate
int x1 = 0;
for( int c=1, end=cols-1; c<cols; c++ )
{
if( (Noise[c]>0) || (c==end) )
{
Noise.Interpolate( x1, c );
x1 = c;
}
}
#ifdef VERBOSE_DEBUG
for( int c=0; c<cols; c++ )
{
if( (Peak[0][c]>Noise[c]) || (Peak[1][c]>Noise[c]) || (Peak[2][c]>Noise[c]) || (Peak[3][c]>Noise[c]) )
Envelope[1][c] = Envelope[0][c];
Envelope[2][c] = Noise[c];
}
char name[64];
std::sprintf( name, "peaks_and_noise%d.ztr", n+1 );
Envelope.SaveAs( name );
#endif
// Cleanup
delete pEnvelope;
}
/**
Removes all peaks below noise floor from the 4*SAMPLES Peak matrix
*/
void MutScanPreprocessor::PeakClip()
{
const int rows = 4;
const int cols = Peak.Cols();
for( int r=0; r<rows; r++ )
{
for( int c=0; c<cols; c++ )
{
// Remove peaks below the noise floor
if( (Peak[r][c]>0) && (Peak[r][c]<Noise[c]) )
Peak[r][c] = 0;
}
}
}
/**
Goes through the 1st four rows of the Peak matrix, and produces a 5th
row containing a logical OR of them to give a picket fence of peaks
over all bases.
This data may be used for shoulder and blob detection which looks for
peak spacing irregularities.
*/
void MutScanPreprocessor::PeakSpacing()
{
const int rows = 4;
const int cols = Peak.Cols();
for( int c=0; c<cols; c++ )
{
for( int r=0; r<rows; r++ )
{
if( Peak[r][c] > 0 )
{
Peak[rows][c] = 1;
break;
}
}
}
}
/**
Most blob problems are avoided because they also occur on the reference.
Elimate peaks caused by gel blobs. A simple peak width measurement
is not sufficient as this will also catch two identical and adjacent
bases if one peak happens to be a shoulder.
A peak width measurement plus a total peak count over that width is
also inconclusive.
Blobs often occur very close to other bases, so this is the measure
we use - to look for unusually close peak spacings and then we examine
these regions in more depth.
The total logical OR of peaks are computed in the last row of the peaks
matrix.
*/
/**
Counts the peaks for each base, ie in each row of Peaks[][].
*/
void MutScanPreprocessor::CountPeaks()
{
const int rows = 4;
const int cols = Peak.Cols();
// Allocate and initialise peak count vector
PeakCount.Create( rows );
PeakCount.Fill( 0 );
// Count all peaks
for( int r=0; r<rows; r++ )
{
int cnt = 0;
for( int c=0; c<cols; c++ )
{
if( Peak[r][c] > 0 )
cnt++;
}
PeakCount[r] = cnt;
}
// Compute maximum number of peaks overall
PeakCountMax = PeakCount.Max();
}
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