U.S. patent application number 15/729506 was filed with the patent office on 2018-04-05 for calibrating the positions of a rotating and translating two-dimensional scanner.
The applicant listed for this patent is APPLIED BIOSYSTEMS, LLC. Invention is credited to John David Morgenthaler, Alan R. Stanford, David Woo.
Application Number | 20180094912 15/729506 |
Document ID | / |
Family ID | 39795793 |
Filed Date | 2018-04-05 |
United States Patent
Application |
20180094912 |
Kind Code |
A1 |
Stanford; Alan R. ; et
al. |
April 5, 2018 |
Calibrating The Positions Of A Rotating And Translating
Two-Dimensional Scanner
Abstract
Systems and methods are provided that comprise calibration
techniques and associated systems that identify the two-dimensional
position, or other alignment or positioning, of sample wells or
other calibration objects located in a sample well plate, or other
surface or area of interest. In some embodiments, calibration of
the plate and/or positioning and/or alignment with respect to
detection optics can be performed in multiple stages for two or
more dimensions.
Inventors: |
Stanford; Alan R.; (Eaton,
OH) ; Woo; David; (Foster City, CA) ;
Morgenthaler; John David; (Menlo Park, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
APPLIED BIOSYSTEMS, LLC |
Carlsbad |
CA |
US |
|
|
Family ID: |
39795793 |
Appl. No.: |
15/729506 |
Filed: |
October 10, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12875995 |
Sep 3, 2010 |
9784563 |
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15729506 |
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12021000 |
Jan 28, 2008 |
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12875995 |
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60898281 |
Jan 30, 2007 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B01L 9/523 20130101;
G01B 11/002 20130101; G01B 11/26 20130101; G01N 35/00584
20130101 |
International
Class: |
G01B 11/00 20060101
G01B011/00; G01B 11/26 20060101 G01B011/26 |
Claims
1. A method of calibrating an alignment of a biological sample
support using a system comprising a spectral photodetector,
comprising: receiving fluorescent emission data from calibration
objects of the sample support; determining a center of a set of the
calibration objects in a first dimension; determining a set of
translations of the calibration objects in a second dimension;
generating a calibrated alignment of the calibration objects based
on the center and the determined set of translations.
2. The method of claim 1, wherein determining a center comprises
determining a center corresponding to an angular position of an
imaging element imaging the calibration objects.
3. The method of claim 2, wherein determining a center comprises
summing or differencing a set of peaks in the emission data for the
set of calibration objects in the second dimension at the same
angular value.
4. The method of claim 3, wherein determining a center comprises
identifying a highest summation of emission data in the second
dimension, and associating the center with the angular value
corresponding the highest summation of emission data.
5. The method of claim 1, wherein determining a set of translations
comprises identifying a set of peaks in the emission data for a set
of calibration objects in the second dimension.
6. The method of claim 1, further comprising generating a
statistical measure of the separation distance between pairs of the
set of calibration objects.
7. A system for calibrating an alignment of a sample support and a
detection device, comprising: an input unit, the input unit being
configured to receive fluorescent emission data from calibration
objects of the sample support; and a processor unit, the processor
unit communicating with the input unit and being configured to:
determine a center of a set of the calibration objects in a first
dimension, determine a set of translations of the calibration
objects in a second dimension, and generate a calibrated alignment
of the calibration objects based on the center and the determined
set of translations, wherein the calibrated alignment is configured
to be used to calibrate the system to analyze a plurality of
biological samples contained within the calibration objects.
8. The system of claim 7, wherein determining a center comprises
determining a center corresponding to an angular position of an
imaging element imaging the calibration objects.
9. The system of claim 7, wherein determining a set of translations
comprises identifying a set of peaks in the emission data for a set
of calibration objects in the second dimension.
10. The system of claim 7, further comprising generating a
statistical measure of the separation distance between pairs of the
set of calibration objects.
11. A calibrated representation of the position of calibration
objects of a sample support for use by a diagnostic instrument, the
calibrated representation being generated by a method comprising:
receiving fluorescent emission data from calibration objects of the
sample support; determining a center of a set of the calibration
objects in a first dimension; determining a set of translations of
the calibration objects in a second dimension; generating a
calibrated alignment of the calibration objects based on the center
and the determined set of translations to calibrate the diagnostic
instrument to analyze a plurality of samples contained within the
calibration objects.
12. The calibrated representation of claim 11, wherein determining
a center comprises determining a center corresponding to an angular
position of an imaging element imaging the calibration objects.
13. The calibrated representation of claim 11, wherein determining
a set of translations comprises identifying a set of peaks in the
emission data for a set of calibration objects in the second
dimension.
14. The calibrated representation of claim 13, wherein the set of
translations in the second dimension comprises a set of linear
offsets.
15. The calibrated representation of claim 11, wherein the method
further comprises generating a statistical measure of the
separation distance between pairs of the set of calibration
objects.
16. The calibrated representation of claim 11, wherein the
calibration objects comprise a set of sample wells.
17. (canceled)
18. (canceled)
19. (canceled)
20. The calibrated representation of claim 11, wherein the sample
support comprises a plate.
21. The method of claim 1, wherein the calibration objects comprise
sample wells configured to contain biological samples.
22. The system of claim 7, wherein the calibration objects comprise
sample wells.
23. The system of claim 7, wherein the sample support comprises a
plate.
Description
RELATED APPLICATION
[0001] This application in a continuation of U.S. patent
application Ser. No. 12/875,995 filed Sep. 3, 2010, which is a
continuation of U.S. patent application Ser. No. 12/021,000 filed
Jan. 28, 2008, which claims priority to U.S. Provisional
Application No. 60/898,281 filed Jan. 30, 2007, entitled
"Calibrating the Positions of a Rotating and Translating
Two-Dimensional Scanner," all of which are incorporated herein in
its entirety by reference.
BACKGROUND
[0002] Polymerase chain reaction (PCR) and other detection systems
rely upon the accurate and consistent positioning of sample well
plates, and other carriers or supports, to perform accurate
measurements of sample fluorescence in arrays of sample wells. When
the 96 or other number of sample wells in a standard microtitre
plate, or other plate configuration, are not accurately aligned
with the read path of the optical detector, the peak signal
intensities associated with individual wells can be incorrectly
measured and recorded. Systems employing spectral filters on the
detection optics can likewise experience spectral shifts when the
filter optics are skewed from desired alignments. Other detection
artifacts can occur when the detection or imaging optics are not
accurately aligned with the sample wells, or other detection
regions. Correct detection and alignment of the optical reader with
the sample wells is a significant objective for these and other
detection systems.
SUMMARY
[0003] According to various embodiments of the present teachings,
systems and methods are provided which scan or image the sample
wells of a sample plate, or other calibration objects or features,
and capture the fluorescent dye or other emission amplitudes and
spectra to generate an accurate positional calibration or alignment
setting of the plate and wells or other calibration objects. In
some embodiments, the sample wells can be loaded with reference
fluorescent dyes, and, for example, scanned using a photodiode or
other detection device, to record intensity peaks and locations.
The photodiode or other detection devices can be mounted in a
rotating scan head which can move across the plate in an arc
pattern to locate over individual columns in a sample well grid.
The scan head can also move in a translational direction, for
example, up and down along columns or lines, to detect the
successive rows, or other sample supports, or other features of
well emissions.
[0004] According to various embodiments, the raw scanned or imaged
data can contain positional or geometric distortions, because the
scan head moves along an arc-shaped rotational sweep as it moves in
its angular degree of freedom. In some embodiments, the calibration
analysis can locate peak pixels of individual wells, and determine
the average or mean separation of the wells in an effort to
calibrate, shift, or realign the well peaks to produce a
non-distorted representation of the sample plate, and the wells in
the sample plate. Subsequent scans of the samples wells conducted,
for example, during PCR or other operational runs, can make use of
the calibrated plate alignment to simplify optical scans by taking
intensity readings along only the calibrated column and row
coordinates. The speed and accuracy of data collection can be
increased, among other advantages.
FIGURES
[0005] FIG. 1 illustrates rotating and translating a
two-dimensional scanner, according to various embodiments of the
present teachings.
[0006] FIG. 2 illustrates a rotation calibration image including a
distorted image of a rectangular grid of objects, according to
various embodiments of the present teachings.
[0007] FIG. 3 illustrates a graph of image intensities summed along
the direction of translation, according to various embodiments of
the present teachings.
[0008] FIG. 4 illustrates a graph of image intensities of a single
column of a rotation calibration image, according to various
embodiments of the present teachings.
[0009] FIG. 5 illustrates a translation calibration image,
according to various embodiments of the present teachings.
[0010] FIG. 6 illustrates a graph of image intensities across the
direction of rotation, according to various embodiments of the
present teachings.
[0011] FIGS. 7(A) and 7(B) illustrate a flowchart of peak detection
and processing, according to various embodiments of the present
teachings.
DESCRIPTION
[0012] According to various embodiments of the present teachings,
calibration of the output signal location readings of a sample well
plate, can be performed to maximize the accuracy and consistency of
spectral and/or other readings. In some embodiments, the
calibration can be conducted using a sample well plate and an
associated optical reader which can be or can comprise a real-time
polymerase chain reaction (PCR), or other system. According to
various embodiments, the calibration systems and methods can be
implemented in or applied to PCR scanning systems in which a read
head containing a photodetector, for example, a photodiode or other
detector, can read the fluorescent output or other output from a
single well or location at a time, then travel to a next well or
location to read the spectral dye or other output at that location,
and step or repeat across a plate or other container or platform to
take spectra from the entire group of sample wells. The calibration
systems and methods can be implemented in or applied to PCR imaging
system, in which a photodetector, for example, a CCD, CID or other
detector, images an entire plate and all sample wells contained
therein at one time or substantially one time, for instance, taking
a spectral image of all 96 or other number of wells of a standard
microtitre plate. According to various embodiments, each well or
other container or location in a plate or other platform can
contain samples, for example, samples of DNA fragments or other
material, to which one or more spectrally distinct dyes can be
attached for detection and analysis.
[0013] Herein, the term "emission" is used to exemplify a signal
detected and/or calibrated according to various embodiments of the
present teachings. It is to be understood that by "emission" the
present teachings are referring to not only electromagnetic
radiation but rather are also referring to any physical or chemical
signal or other data that can be read, detected, imaged, or
surmised from one or more area of interest, for example, a support
region such as a well of a multi-well plate. "Emission" herein is
intended to encompass electromagnetic radiation, optical signals,
chemiluminescent signals, fluorescent signals, radiation
transmission values, and radiation absorption values.
[0014] According to various embodiments, for example, as generally
depicted in FIG. 1, the calibration can comprise rotating and
translating a two-dimensional scanner 102 that moves a set of
imagers 104 across an area of interest on a sample well plate 106
or other surface or support. According to various embodiments, each
of the set of imagers 104 can comprise a single-pixel imager
element, for example, a photodiode. Each of the set of imagers 104
can comprise a multiple-pixel imager element, for example, a charge
coupled device (CCD). According to various embodiments, other
imaging elements and arrangements of those elements can be used,
for example, a photomultiplier tube. According to various
embodiments, each set of imagers 104 can comprise, as shown, a set
of three imagers, and each can be equipped with a distinct spectral
filter, to filter and image emission of different wavelengths
resulting from the imaged samples. Different amounts of filters can
be used.
[0015] According to various embodiments, the area of interest on
sample well plate 106 can contain, for example, a precision
rectangular grid of calibration objects, such as the regularly
spaced sample wells 108 of sample plate 106, as shown. The wells
108 or other calibration objects can be used, for example, for PCR
or other amplification or other reactions. As shown, instrument
fixtures such as a mounting block, heater block, or other structure
or support in which plate 106 can be mounted or registered, can
align one axis of the rectangular grid of wells 108 or other
calibration objects with the translational motion of scanner
102.
[0016] According to various embodiments, the scanner 102 can be
calibrated, for example, to accurately move to positions centered
on the wells 108 or other calibration objects in the rectangular
grid of plate 106, or other surface or sample support. The
calibration analysis can comprise inspecting at least two images
taken of plate 106 and/or wells 108, and computing the rotational
and translational positions of the array of wells 108, which
correspond to positions in the rectangular grid of plate 106 or
locations in another array or pattern.
[0017] According to various embodiments, the calibration analysis
can comprise acquiring every column of the at least two images
inspected by rotating the head of the scanner 102 to an angular or
rotational position (labeled .theta., theta), by holding that
rotational position, by translating to a start position, by
acquiring image pixels of plate 106 or other objects, by
translating to a stop position, and by finishing the acquisition of
image pixels of plate 106 or other objects. The motion of the scan
head of scanner 102 can be step-wise, for example, using a stepper
motor to rotate or translate the head of scanner 102. The motion of
the scan head of scanner 102 can be continuous, without
intermittent start and stop actions. According to various
embodiments, all columns of the rotational calibration image taken
of plate 106 can begin and stop at the same translational or linear
position, but can have different rotational and/or angular
positions. The rotational or angular position can be represented by
angle .theta. (theta), or other parameter. According to various
embodiments, the rotational (.theta.) measurement positions across
plate 106 can be uniformly spaced, for example, as the head of the
scanner 102 traces an arc which lines up with columns of plate 106.
As the set of imagers 104 moves across plate 106 and takes images
of emissions from wells 108 or other calibration objects, a
distorted image of the rectangular grid of objects from each filter
can result, for example, as illustrated in FIG. 2.
[0018] According to various embodiments, the column coordinate can
be defined as the rotational position (.theta.) at which a pixel is
acquired. In some embodiments, the row coordinate can be defined as
the translational position at which a pixel was acquired. According
to various embodiments, the column coordinates of the objects in
the same row of rectangular grid of wells 108 (e.g., the first
object in the columns) can form an arc or curve in the raw
image.
[0019] According to various embodiments, the calibration can
comprise a first calibration or processing stage, to determine the
rotational (.theta.) positions of the centers of the wells 108, or
other calibration objects. The calibration analysis can comprise
summing the image intensities for emissions from each well 108,
detected in each column of plate 106, at a single rotational
(.theta.) position along the direction of linear translation of
scanner 102. A typical result of this summation is illustrated, for
example, in FIG. 3. In various embodiments as shown, the positions
of the detected signal peaks correspond to the rotational centers
of the wells 108, because the brightest of most intensity signal
amplitudes combine down the centerline of a column of wells 108.
This analysis, in one regard, can more accurately anchor or locate
the angular or rotational (.theta.) positions of well columns in
plate 106. Differencing the image intensities for emissions from
each well 108, detected in each column of plate 106, at a single
rotational (.theta.) position along the direction of linear
translation of scanner 102, can instead or additionally be used to
determine the rotational centers of the wells.
[0020] According to various embodiments, the calibration analysis
can comprise a second calibration or processing stage, which can
compute the column-dependant translational coordinates, which in
contrast to rotational coordinates, will produce an undistorted
image. The calibration analysis can find or detect the row
positions (translational coordinates) of wells 108, or other
calibration objects. These positions correspond to peak locations
of wells 108 in single columns of the rotational calibration image.
Conversely, the column positions correspond to rotational centers
of columns of wells 108. FIG. 4, for example, shows one such single
column of the rotational calibration image, including a set of
peaks associated with emissions from successive rows which can be
encountered in a column, according to various embodiments.
[0021] According to various embodiments, the calibration analysis
can comprise a third calibration or processing stage, which can
inspect a new or further image, the "translation calibration
image," to determine or adjust the translational positions of the
calibration objects. An exemplary translation calibration image is
illustrated, for example, in FIG. 5.
[0022] According to various embodiments, the results of the first
and second steps or stages can create a list of initial and final
translational positions. In some embodiments, one list can be
created for each column (rotational position) of the sample wells
108, or other calibration objects. The initial and final positions
can be offset from, or correspond to, the first and last wells 108
by a distance equal to the average within-column (translational)
separation of all the wells 108, or other calibration objects.
[0023] According to various embodiments, the calibration analysis
can comprise generating or manipulating a translation calibration
image containing an equal amount of columns as there are columns of
wells 108, or other calibration objects in original plate 106, with
offsets to remove the arcing present in the original raw plate
image. Each image column is centered on a different column of wells
108 or other calibration objects. The peak intensities in each
column of the translation calibration image can correspond to the
translational centers of the wells 108 or other calibration
objects. FIG. 6, for example, illustrates one column of the
translation calibration image, after translational offset or
adjustment.
[0024] According to various embodiments, once the column positions
have been accurately determined, processing of PCR or other runs
can be performed using one image line, which can proceed down the
determined center of each well for each column, with sample peaks
determined from that single position. Actual processing runs can
use the same or different optical resolution settings as the
positional calibration processing. According to various
embodiments, the PCR or other processing runs can, for instance,
use a lower resolution to capture raw peak data, in part because
there is increased confidence regarding data accuracy once
positional calibration has been performed. One peak or amplitude
can be captured for each well or other sample support or area of
interest. In some embodiments, multiple intensity data points can
be captured for each well.
[0025] According to various embodiments, each of rotational
(column-oriented) and row alignment calibrations can be performed
together. In some embodiments, each of rotational and row alignment
calibrations can be performed at different times, or frequencies.
In some embodiments, rotational (column-oriented) calibration can
be performed with less frequency on a given PCR or other machine
than row-alignment calibration. In some embodiments, row-alignment
calibration can be performed before each analytic run, or at other
times.
[0026] According to various embodiments, the calibration analysis
can comprise utilizing techniques to find peaks in all the
signatures, for example, two signatures in the rotation calibration
analysis, and one signature in the translation calibration image.
The technique used to identify peaks can comprise a type of
recursive processing techniques referred to herein as a "peak
splitter" algorithm or module, a flowchart of which is illustrated,
for example, in FIGS. 7A and 7B.
[0027] According to various embodiments, the peak splitter
algorithm or module used to identify intensity peaks from
individual wells 108 can consider averages of n-pixel wide segments
of the intensity signature. The peak splitter algorithm or module
can begin in step 702. In step 704, the first two adjacent segments
(e.g., samples 1 to n and n+1 to 2n) can be accessed or retrieved,
for instance, from a PCR or other machine, from a stored source,
from a networked source, or from other data sources or stores. In
step 706, the difference between the averages of the first and of
the second n-pixel wide segments can be computed to determine the
initial direction. In step 708, according to various embodiments,
the peak splitter can perform an "extender" function or module that
moves the two adjacent segments towards the end of the signature,
by one sample. In step 710, once the adjacent segments are shifted
or moved, the current direction can become the difference between
the averages of the current first and of the current second
adjacent segments. In step 712, a test can be administered to
determine whether the current and initial directions are the same.
If the directions are the same, processing can return to step 708.
If the directions are different, processing can proceed to step
714.
[0028] According to various embodiments, when the updated and
initial directions differ, the extender function or module can
perform further tests. In step 714, a test can be administered to
determine whether the number of samples spanned by the initial
first segment and the current final segment is greater than or
equal to an adjustable, dynamically calculated, or predetermined
threshold number of samples. If the number of samples spanned is
greater than the threshold number of samples, processing can
proceed to step 718 where the extender function or module can
declare a transition. According to various embodiments, when the
extender function or module declares a transition, in step 720, the
extender can save the sample indices of the initial segment and the
current final segments, and in step 722, it can return the part of
the signal that begins one sample past the first sample of the
current final segment.
[0029] According to various embodiments, if the number of samples
determined to be spanned by the initial first segment and the
current final segment in step 714 is less than the adjustable,
dynamically calculated, or predetermined threshold number of
samples, the extender function or module can proceed to step 716
where it can set the initial direction computed from the current
two adjacent segments, and return to step 706. The peak splitter
algorithm or module can repeatedly call or execute the extender
function or module until the extender has exhausted all the sample
wells 108 or other calibration objects in the signature. In some
embodiments, each pass through the extender processes only the part
of the signal returned by the previous pass through the
extender.
[0030] According to various embodiments, once the extender
processing has finished, in step 724, the peak splitter algorithm
or module can invoke or execute a "compute peaks" function or
module, which can parse the list of transitions found by the
extender. In step 726, if the adjacent transitions declared by the
extender are increasing, then followed by a decreasing region, and
the transitions or other features are separated by less than an
adjustable, dynamically calculated, or predetermined threshold
number of samples, the compute peaks function or module can declare
candidate peaks. In step 728, for each candidate peak, the compute
peaks function or module can create a mathematical model of the
transition, for example, by computing a least squares quadratic
fit. As an example, a least squares quadratic fit to samples in
adjacent transitions can be computed. The maximum value of the
model can be considered the peak intensity. In step 730, according
to various embodiments, the peak position and intensity can be
saved, for example, to electronic memory, local hard disk, or
network storage, or other memory or storage device.
[0031] In step 732, according to various embodiments, the
calibration analysis can comprise, after processing all the
transitions, the compute peaks function or module which can make a
determination whether the number of peaks found exceeds an
adjustable, dynamically calculated, or predetermined peak number
threshold. If in step 732 a determination has been made that too
few peaks were discovered, for example, a number below a peak
number threshold, for instance, the total number of wells 108, half
of the total number of wells 108, or another number or threshold,
then in step 734 the compute peaks function or module can declare
an error, after which processing can end, repeat, return to a prior
processing point, or proceed to a further processing point in step
738. If an error or anomaly is declared, detected or suspected, the
calibration analysis can comprise corrections and/or compensations
for the error.
[0032] According to various embodiments, if in step 732 a
determination is made that too many peaks have been discovered
above a number of an adjustable, dynamically calculated, or
predetermined maximum peak threshold, then in step 736 the compute
peaks function or module can execute a "determine best peaks"
function or module. In step 736, the determine best peaks function
or module can iteratively remove the smallest peaks, for example,
until a desired, adjustable, dynamically calculated, or
predetermined number of peaks remain, or until a statistical
measure, for example, a z-score or standard deviation among
remaining peaks, satisfy a desired, adjustable, dynamically
calculated, or predetermined threshold or criterion. After the best
peaks processing is complete, processing can end, repeat, return to
a prior processing point, or proceed to a further processing point
in step 738.
[0033] According to various embodiments, the positions of the wells
108 or other calibration objects in the rectangular grid or pattern
or array in plate 106, can be tightly controlled during
manufacture, allowing the calibration analysis to assume well
separations and other measures are rigidly and accurately known,
and therefore apply statistical tests to the rotational and
translational positions that are computed. Results that fail these
tests can indicate poor calibration procedures. If an error is
detected or suspected, the calibration analysis can comprise
correction and/or compensation for, and/or eliminate the error. In
some embodiments, the calibration analysis can comprise a
statistical z-score test, or other metric to validate features of
the calibration analysis, for example, the separation of the
columns in plate 106. Any column separation, for example, with a
z-score less than an adjustable, dynamically calculated, or
predetermined threshold, can indicate poor calibration procedures
or results.
[0034] According to various embodiments, after finding and
validating the column positions (rotational coordinates) of the
wells 108 or other calibration objects, the calibration analysis
can comprise, computing the column-dependant translational
coordinates that will produce an undistorted or realigned image,
for example, as illustrated in FIG. 5. To accomplish this, the
calibration can comprise determining the row positions
(translational coordinates) of the wells 108 or other calibration
objects.
[0035] According to various embodiments, for each column position
determined from the rotation calibration image (e.g., as
illustrated in FIG. 2), that column of data obtained can be
transmitted, as a signature, to the peak splitter algorithm or
module. The peak splitter can compute the column coordinates
(translational positions) of the peaks in the column signature.
These positions can correspond to the positions in the column of
the wells 108, or other calibration objects.
[0036] According to various embodiments, the calibration analysis
can comprise computing, for each column position, the average
translational separation of the wells 108 or other calibration
objects, and subjecting these separations to a z-score or other
test. In some embodiments, z-scores greater than an adjustable,
dynamically calculated, or predetermined value can indicate poor
calibration results.
[0037] According to various embodiments, the undistorted or
realigned scan for each column can begin one separation before and
one separation after the first and last well 108 in the column.
Unique start and stop positions can be computed for each column.
These start and stop positions can produce an undistorted or
realigned image (e.g., as illustrated in FIG. 5) which has only as
many image columns as there are columns of wells 108 or other
calibration objects. According to various embodiments, the
calibration analysis can comprise utilizing the processes described
above to extract the translational positions of the wells 108 or
other calibration objects.
[0038] According to various embodiments, as with the rotational and
translational positions computed from the rotation calibration
image (illustrated, e.g., in FIG. 2), the calibration can comprise
applying a z-score test to the translational positions from the
translation calibration image (e.g., as illustrated in FIG. 5).
Z-scores greater than an adjustable, dynamically calculated, or
predetermined threshold can indicate poor calibration results. In
some embodiments, other statistical measures than z-scores can be
used to threshold or analyze rotational, translational, or other
position data.
[0039] According to various embodiments, different aspects of
differential dissociation/melting curve analyses, and different
aspects of the present teachings, can be applied to commercial
systems and implementations, such as the Step One.TM. machine
commercially available from Applied Biosystems, Foster City,
Calif., and described, for example, in the publication entitled
"Applied Biosystems Step One Real-Time PCR System Getting Started
Guide," which is incorporated by reference in its entirety
herein.
[0040] It will be appreciated that while various embodiments
described above involve the calibration of one or more aspects of
plate positioning and instrument reading, according to various
embodiments more than one type of calibration can be performed,
together or in sequence. While various aspects of the present
teachings have been described with regard to calibration in one
angular and one linear or translational direction or dimension, it
will be appreciated that according to various embodiments,
calibration can, for example, be performed in two linear
dimensions. According to various embodiments, calibration can
likewise be performed in three dimensions, for example including a
vertical displacement. Calibration according to other geometric
directions, dimensions, or properties can also be performed.
[0041] Various embodiments of the present teachings can be
implemented, in whole or part, in digital electronic circuitry,
optics, optronics, or in computer hardware, firmware, software, or
in combinations thereof. Apparatus of the present teachings can be
implemented in a computer program, software, code, or algorithm
embodied in machine-readable media, such as electronic memory,
CD-ROM or DVD discs, hard drives, or other storage device or media,
for execution by a programmable processor. Various method steps
according to the present teachings can be performed by a
programmable processor executing a program of instructions to
perform functions and processes according to the present teachings,
by operating on input data and generating output. The present
teachings can, for example, be implemented in one or more computer
programs that are executable on a programmable system including at
least one programmable processor coupled to receive data and
instructions from, and to transmit data and instructions to, a data
storage system or memory, at least one input device such as a
keyboard and mouse, and at least one output device, such as, for
example, a display or printer. Each computer program, algorithm,
software, or code can be implemented in a high-level procedural or
object-oriented programming language, or in assembly, machine, or
other low-level language if desired. According to various
embodiments, the code or language can be a compiled, interpreted,
or otherwise processed for execution.
[0042] Various processes, methods, techniques, and algorithms can
be executed on processors that can include, by way of example, both
general and special purpose microprocessors, such as, for example,
general-purpose microprocessors such as those manufactured by Intel
Corp. or AMD Inc., digital signal processors, programmable
controllers, or other processors or devices. In some embodiments,
generally, a processor will receive instructions and data from a
read-only memory and/or a random access memory. In some
embodiments, a computer implementing one or more aspects of the
present teachings can generally include one or more mass storage
devices for storing data files, such as magnetic disks, internal
hard disks, removable disks, magneto-optical disks, and CD-ROM DVD,
Blu-Ray, or other optical disks or media. Memory or storage devices
suitable for storing, encoding, or embodying computer program
instructions or software and data can include, for instance, all
forms of volatile and non-volatile memory, including for example
semiconductor memory devices, such as random access memory,
electronically programmable memory (EPROM), electronically erasable
programmable memory, EEPROM, and flash memory devices, as well as
magnetic disks internal hard disks, removable disks,
magneto-optical disks, and optical disks. Any of the foregoing can
be supplemented by, or incorporated in, ASICs. In some embodiments,
processors, workstations, personal computers, storage arrays,
servers, and other computer, information, or communication
resources used to implement features of the present teachings can
be networked or network-accessible.
[0043] Other embodiments will be apparent to those skilled in the
art from consideration of the present specification and practice of
the present teachings disclosed herein. For instance, while the
various embodiments of the present teachings have been described as
involving the positional calibration of sample plates in angular or
polar terms, according to various embodiments, the present
teachings can be applied to systems or techniques configured in
[x,y] coordinates, or other coordinate systems. Similarly, while
various embodiments have been described as related to aligning the
planar orientation of a plate in a PCR machine, according to
various embodiments, vertical alignment, or three-dimensional
alignment, can be carried out according to the present
teachings.
[0044] Likewise, while various embodiments have illustrated plate
positioning and well detection in terms of a plate 106 having a
regular, rectangular array of wells 108, according to various
embodiments other patterns or groupings of wells 108, for example,
circular, square, triangular, complex or irregular shapes or
configurations of wells 108, can be used. Positional calibration,
according to the present teachings, can, moreover, be carried out
in detection systems other than PCR instruments. Resources
described in various embodiments as singular can, in embodiments,
be implemented as multiple or distributed, and resources described
in various embodiments as distributed can be combined. It is
intended that the present specification and examples be considered
as exemplary only.
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