MCGH Analyzer
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Transcript MCGH Analyzer
MCGH Analyzer
Hans A. Kestler
André Müller
08-10-2004
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Data processing steps
• Scanning of the DNA chips (normal and
switched)
– 2 Channels (Cy 5 and Cy 3)
• Build mean/median over the pixels
• Further processing with MCGH Software
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MCGH software
• Background reduction
calculate intensities according to the background
• Quality control of the spots
reject spots not fitting the quality criteria
• Accumulate spots to clones
• Check test
reject clones not fitting the visual options
• Select control clones
• Reduce control clones
• Main calculation loop
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Overview
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Background reduction
Background reduction to get intensities
1.
2.
3.
4.
5.
6.
No reduction
Fixed reduction
Local reduction
Global reduction
Local + Fixed reduction
Global + Fixed reduction
Compute log Ratios
•
•
log( IntCy3 / IntCy5 )
log( IntCy5 / IntCy3 )
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Quality control
Reject spots with
• flags marked by the scanning software
(bad, not found, absent, normal ...)
• A background intensity brighter than the
foreground (new!)
• Min/Max reduction:
–
–
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Reject the n smallest ratios
Reject the n largest ratios
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Spots to clones
Accumulate the non-rejected spot values
•
Mean
•
Standard deviation
•
Median
over
•
Intensities (Cy3, Cy5)
•
log Ratios
New Feature:
Reject clones with less than SpotLowerBound valid spots.
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Check test
Reject clones if at least one of these conditions holds:
1.
2.
3.
Me(di)an background intensity > Background upper bound
Me(di)an Cy3 Intensity < Me(di)an Cy3 background intensity x
Intensity lower bound
Standard deviation Cy3 Ratio > Ratio SD upper bound
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Select control clones
Only non-rejected clones will be selected as control clones.
•
Manual selection
Select clones with id = ‚91‘ or ‚k‘ or ‚K‘ or ‚?91‘ as control clone
•
Automatic selection
–
No [AutoBand]
[CutoffPercentage] clones
from the middle band
–
[AutoBand]
Select band around the median
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Reduce control clones
Some of the control clones will be rejected ...
•
[Cutoff Percentage]
Reject the n smallest ratios
•
Without [Cutoff Band]
Reject the n largest ratios
•
[Cutoff Band]
Reject band around the median
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Main calculation loop
1.
2.
3.
Calculate control means (the mean/median over all control clones/spots)
Normalize ratios (subtract control mean from the ratio)
Calculate tolerance value T
2s 2
T t2n2,1
n
s standard deviation of the ratios of the observed clone
n the number of valid spots in this clone
t value of the t-statistic
significance niveau
4.
[ Force T-Test ]
Reject clones with T > [ Force T Value ]
5.
[ C Check ]
6.
Replace tolerance values with possible greater values.
Find clone with maximum tolerance and reject it if its tolerance value T is > [ Force
T Value ]
7.
Perform [ T Test ] and evaluate result value.
Everything has to be recalculated if a control clone will be rejected.
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The C Check
The clone tolerance values are now recalculated according to the following scheme:
mc
mean overcontrolspot ratios
sc2
varianceovercontrolspot ratios
nc
number of controlspots
mr
mean over ratiosof thecurrentclone
sr2
varianceover ratiosof thecurrentclone
nr
number of validspotsin thisclone
Tnew tnc nr 2,1
(nr 1) sr (nc 1) sc nc nr
mr mc
nc nr 2
nc nr
If the new tolerance value is greater than the old T will be replaced by the new value
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The T Test
If [ Force T ] is set, the value Tˆ will be set to the [ Force T Value ]
otherwise it is the greates tolerance value found in the clones.
mc
mean overcontrolspot ratios
sc2
varianceovercontrolspot ratios
nc
number of controlspots
mr
mean over ratiosof thecurrentclone
s
2
r
nr
z1
varianceover ratiosof thecurrentclone
z2
number of validspotsin thisclone
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mc Tˆ mr
(nr 1) sr (nc 1) sc nc nr
nc nr 2
nc nr
mc Tˆ mr
(nr 1) sr (nc 1) sc nc nr
nc nr 2
nc nr
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The T Test (2)
Calculation of the result value R
• [ T Test ]
R 0 mc mr Tˆ mc mr Tˆ z1 t nc nr 2,1 z2 t nc nr 2,1
R 1 mc mr
R 1 mc mr
•
No [ T Test ] : thresholding
R 0 mc mr t mc mr t
R 1 mc mr t
t
negativethresholdvalue
t
positivethresholdvalue
R 1 mc mr t
In this routine the test T > [ Force T Value ] will be performed repeatedly
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NCBI Clone Database
• Integration of the NCBI “component”
database
• Automatically mapping of clone id’s to
accession numbers, genomic clone locations
and clone status information according to an
up-to-date database
• Direct import of the NCBI file format
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Database-generated Information
Accession
-Number
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Start-Base
End-Base
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Clone-State
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Batch Processing
•One ore more file pairs can
be added to a session
•All computations are
performed simultaneous on
the included datasets
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Diagrams functions
• Ratio-profiles of multiple clone sets can be shown in one
diagram
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Ideogram Browser 1
• Independent portable Java application
• Automation from MCGH-Analyzer with JNI
• Generation of ideogram drawings from the NCBI
map database
• Direct representation of gain and lost markers of
multiple clone sets
• Scalable and scrollable graphs
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Ideogram Browser 2
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Software Structure 1
• Excel as convenient platform with widely known
user interface for
– Table representation
– Diagram drawing
– User interaction
• Windows DLL written in C++ for high
performance using COM automation
• Platform-independent Java-Application for
visualizing ideograms (can be docked to the DLL
via JNI)
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Software Structure 2
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Future Features
• Copy number estimation
– Global thresholds
– Adaptive (local) thresholds
• Wavelets
• Adaptive weights smoothing
• NCBI database online update
• Interface to the R platform
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