Agilent QC Chart Tool 3.5 User Manual
Agilent
QC Chart Tool 3.5
User Guide
For Research Use Only. Not for use in
diagnostic procedures.
Agilent Technologies
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G4460-90048
Edition
Revision C0, January 2021
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This guide is valid for 3.5 and later revisions
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superseded.
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QC Chart Tool
In This Guide...
This guide describes how use the Agilent QC Chart Tool
software to query, filter, and evaluate microarray extractions.
It also describes how to visualize current and historical
batch microarray extraction processes.
1 Getting Started
This chapter gives an overview of how to use the software to
evaluate microarray extraction quality. It gives instructions
for how to do common tasks.
2 Building Queries, Metric Sets, and Charts to Evaluate Extractions
This chapter describes how Queries are applied to
extractions, how Metric Sets are built and used to filter and
evaluate extractions, and how to visualize batch processes
using Charts.
3 QC Chart Tool Reference
This chapter describes the parts of the Agilent QC Chart
Tool main window that you use to query and evaluate
microarray extractions. It also describes any dialog boxes
that appear during quality evaluation of the extractions.
QC Chart Tool 3
4 QC Chart Tool
Contents
1 Getting Started 7
What Is the QC Chart Tool Software? 8
Example use cases 9
2 Building Queries, Metric Sets, and Charts to Evaluate Extractions 15
Importing Data 16
To import FE statistics and parameter information 16
To import a query result 17
Building and Running Queries 18
To create a query 18
To create a composite query 19
To edit a query 20
To run a query 21
To delete a query 21
To rename a query 21
To import a query result 22
To export a query result 22
Defining Metrics 23
To create a new metric 23
To delete a metric 24
Defining Metric Sets and Thresholds 25
To create a metric set 25
To edit a metric set 26
To view a metric set 26
To set metric thresholds in metric sets 27
To export metric sets 30
To import metric sets 31
To delete a metric set 31
QC Chart Tool 5
Contents
To remove a metric from a metric set 31
To rename a metric set 32
Producing and Displaying Charts 33
To create a chart 33
To view the chart 34
To edit a chart 34
To delete a chart 34
To rename a chart 35
3 QC Chart Tool Reference 37
The QC Chart Tool Window 38
Command ribbon 39
Navigator 43
Data window 47
Dialog Boxes 52
Agilent Feature Extraction Importer 52
Chart Configuration dialog box 54
Create a new Metric dialog box 55
Delete Metrics 58
Frequency Distribution 59
Metric Set Configuration dialog box: Add Metrics to Metric Set tab 60
Metric Set Configuration dialog box: Selected/Existing Metrics tab 64
Query Builder dialog box 66
6 QC Chart Tool
Agilent QC Chart Tool
User Guide
1
Getting Started
What Is the QC Chart Tool Software? 8
Example use cases 9
This chapter provides an overview of how to use Agilent QC Chart Tool to
query, evaluate, and chart microarray extraction data. For a list of how- to
instructions for the tasks available in the QC Chart Tool software, see
Chapter 2, “Building Queries, Metric Sets, and Charts to Evaluate
Extractions”. For a description of each part of this software, including all
of the dialog boxes that can appear when you click buttons and other
elements, see Chapter 3, “QC Chart Tool Reference”.
Agilent Technologies
7
1Getting Started
What Is the QC Chart Tool Software?
What Is the QC Chart Tool Software?
Agilent QC Chart Tool is installed when you install the Agilent Feature
Extraction software. It analyzes summary statistics from Feature
Extraction output files in order to monitor microarray processing
performance.
The data is kept in the shared Feature Extraction database, that you can
query. Queries enable you to search this data. You can save the queries to
allow the display of specific subsets of the data. For instance, queries can
select the data found in specific designs, batches, or dates of processing.
Using the data, you can create metrics that monitor aspects of the
microarray processing workflow.
Additionally, you can create metric sets that combine metrics, and you can
set thresholds for metrics within a metric set. Agilent includes default
metric sets for each microarray type in the database. These metric sets
were optimized for the workflow using the Agilent microarray scanner,
Feature Extraction default protocols, and Agilent laboratory protocols. You
can change and save a default metric set using a new name, to create one
or more custom metric sets; for example, to optimize the thresholds for
your custom protocols.
With QC Chart Tool, you can select a query to define which extractions to
view and select a metric set to define which metrics to view. You then
graphically plot the results from current or historical microarray data, and
create thresholds for the metrics that are appropriate for your
experimental conditions and processing environment.
The QC Chart Tool software is designed for use in a production
environment where:
• Microarray processing protocols are standardized and you want to
examine the effect of variables on performance related to:
• Operators
• Wet- lab protocols
• FE parameter protocols
• Monitoring run- to- run consistency is an important goal to:
• Identify extractions that fall outside the established normal range
• Identify systematic data trends
8 QC Chart Tool
For the most recent information and to download QC metric sets, go to
the website: www.agilent.com/en/qc- chart- tool- metric- sets.
Example use cases
Feature Extraction generates output to assist in quality assessment. A
table of array- wide, or global statistics (the “Stats” table in FE), is useful
in data quality determination for each extraction. These global statistics
capture information from every independent FE step; for example, the
numbers of outliers, the averages of negative control signal statistics, and
spike- in regression values.
The number of output fields are sometimes cumbersome without a tool for
quality assessment of each extraction. QC Chart Tool captures key global
statistics to use as metrics and create graphs for easy visual assessment of
metrics. Additionally, you can use the metrics that are used for analysis
for specific monitoring requirements.
This section provides several common use cases for the software. Although
these examples are from an earlier version of the software, the use cases
and results are the same in the current software version.
Getting Started 1
Example use cases
Use Case 1
QC Chart Tool 9
Analysis of Feature Extraction output
Feature Extraction analysis is a common way to use the QC Chart Tool
software with everyday extraction monitoring. An example of this type of
analysis was performed using a collection of microarrays from several
experiments.
Some of these microarrays were previously annotated by the operator as
having issues in the labeling, hybridization, and/or washing steps. These
microarrays had poor correlation with their replicate microarray sets, and
were chosen because they each had at least one metric flagged as having
values outside of the normal range.
This analysis of Feature Extraction consisted of:
1 A comparison to all other extractions within the extraction set.
2 A comparison to thresholds associated with the default metric set. For
information on creating metric sets, see “Defining Metrics” on page 23.
1Getting Started
Example use cases
By default, the chart generated by QC Chart Tool shows extractions in the
order they were performed. Because QC Chart Tool has customized
sorting, color- by, and shape- by attributes, it is a powerful tool for
visualizing and highlighting trends in patterns.
Figure 1 confirms the presence of processing artifacts and replicate
microarray outliers. The chart shows that several microarrays have more
than one metric out of normal range (represented by red circles). Values
in range are also displayed (blue triangles). The inset window zooms in on
the “rNegCtrlAveGBSubSig” metric, which is the average of the red- channel
negative- control background- subtracted signals. For more information
about Feature Extraction statistics used for metrics, see the Feature
Extraction User Guide.
Figure 1 Assessment of extraction statistics used for metrics with QC Chart Tool
10 QC Chart Tool
Getting Started 1
Example use cases
Use Case 2
Analysis of the user effect on extraction quality
Often the effects of specific variables on extraction quality are needed in
a production setting. One such variable is the effect of the user. A
retrospective analysis of different users was generated using the following
steps in QC Chart Tool:
1 A query was created to select only those extractions of interest and
applied to a chart as the X- axis. For information on creating queries,
see “Building and Running Queries” on page 18.
2 A two- color gene expression metric set was chosen and applied to the
chart as the Y- axis. For information on creating metric sets, see
“Defining Metric Sets and Thresholds” on page 25.
3 The extractions were then color- coded to reflect the three different
operators who had processed the arrays in those extractions.
Figure 2 on page 12 shows data from microarrays processed by users A
(represented by blue squares), B (red circles), and C (green triangles).
Threshold limits appear in upper right- hand corners and as green lines
within each plot. The inset window zooms in on the
“rNegCtrlAveGBSubSig” metric, which is the average of the red- channel
negative- control background- subtracted signals. For more information
about Extraction statistics used for metrics, see the Feature Extraction
User Guide.
QC Chart Tool 11
1Getting Started
Example use cases
Figure 2 Comparison of the effect of variable users on microarray performance using
QC Chart Tool
Use Case 3
12 QC Chart Tool
Analysis of the effect of changing the FE parameter protocols
Analysis of Extraction statistics used for metrics with the QC Chart Tool
software gives an intuitive evaluation of competing protocol methods, such
as background processing algorithms. An 18- array set was extracted with
either the default FE parameter protocol “Spatial Detrend” background
method or an alternative “Minimum Signal” background method. It was
then processed using the standard metric set in QC Chart Tool.
Figure 3 on page 13 shows extractions with either the default Spatial
Detrend background (represented by blue squares), or the alternate
Minimum Signal background data (red circles). For this data set, more
favorable metric values were clearly seen with the Spatial Detrend method.
This improvement is seen especially with the average negative control
background- subtracted signal, which is closer to the expected value of
zero. It is therefore a more accurate estimate of background.
Getting Started 1
Example use cases
Additionally, under subtraction of background, as seen with the Minimum
Signal method, results in compression of log ratios. The inset window
shows a plot of observed versus expected spike- in ratios (the
“absE1aObsVsExpSlope” metric), where Spatial Detrend background yields
a slope closer to 1.0. For more information about Feature Extraction
statistics used for metrics, see the Feature Extraction User Guide.
Figure 3 Comparison of the effect of FE parameter protocols on extraction quality
QC Chart Tool 13
1Getting Started
Example use cases
14 QC Chart Tool
Agilent QC Chart Tool
User Guide
2
Building Queries, Metric Sets, and
Charts to Evaluate Extractions
Importing Data 16
Building and Running Queries 18
Defining Metrics 23
Defining Metric Sets and Thresholds 25
Producing and Displaying Charts 33
This chapter provides a list of how- to instructions for the tasks available
in the QC Chart Tool software. Most functionality in the QC Chart Tool is
accessible from either the command ribbon or from the object under
consideration in the Navigator.
For a description of each part of this software, including all of the dialog
boxes that can appear when you click buttons and other elements, see
Chapter 3, “QC Chart Tool Reference”.
Agilent Technologies
15
2 Building Queries, Metric Sets, and Charts to Evaluate Extractions
NOTE
Importing Data
Importing Data
This chapter describes how to import data into QC Chart Tool. After
running an extraction in Feature Extraction, you can import quality
information from the extraction manually using the Import function in QC
Chart Tool 3.5.
To import FE statistics and parameter information
1 On the command ribbon, click Import and then click FE Stats and
Parameters. The Import FE Files dialog box appears.
2 Navigate to the Feature Extraction output files.
3 Click Open.
The Agilent Feature Extraction Importer dialog box appears with the
list of selected microarrays.
4 For microarrays that are dye flipped, under Dye Flip, click the arrow
and select Flipped. Otherwise, leave the selection Normal.
5 Click OK.
The FE quality information is added to the available extractions that
you can query and evaluate.
If you import an extraction whose ArrayID (barcode) and ExtractionName are the same as
an extraction in the database, the program prompts you to rename the duplicate extraction,
or ignore it and import the remaining extractions.
If you import an extraction that has the same Array ID (barcode) as another extraction in
the database, you are notified there are duplicate extractions for that barcode. The
extraction is imported as a new row. This can occur if you perform a second feature
extraction on the same image file, or if you washed and reused a microarray.
See Also Refer to “Chapter 3” of the Feature Extraction Reference Guide for a
description of the statistics and parameters that are imported.
16 QC Chart Tool
Building Queries, Metric Sets, and Charts to Evaluate Extractions 2
NOTE
To import a query result
1 On the command ribbon, click Import and then click Query Result. The
Import Query Result dialog box appears.
2 Navigate to a previously exported query result file and click Open.
The program imports the extractions from the query result file. Each
extraction in the file appears as a row in the extraction table.
If there is an extraction in the table that matches an extraction in the query result file, the
extraction row in the extraction table is updated. The existing attribute values in the
extraction table for that row are overwritten with the values from the file. The values of any
attributes that are not present in the query result file will not be updated in the extraction
table.
To import a query result
QC Chart Tool 17
2 Building Queries, Metric Sets, and Charts to Evaluate Extractions
Building and Running Queries
Building and Running Queries
QC Chart Tool has a Query builder where you can create a query for a
subset of the extractions from the Agilent QC Chart Tool database, based
on criteria that you select.
A query is used to define a subset of extractions for a representative data
set, for use in metric and threshold development, and in producing Charts.
One example is a query that contains data from similar biological samples
processed under identical conditions. Another example is to query for
different types of samples or for different processing methods. With the
latter example, you then use the different processing attributes to
color- code a chart. See “Chart Configuration dialog box” on page 54 for
information about using processing attributes. See “Example use cases” on
page 9 for examples of color- coding a chart based on the processing
attributes.
A subset of extractions is defined in a query by specific FEParameter
fields, or by user- added attribute fields.
To create a query
1 To start the query builder, on the command ribbon, click Queries and
then click New.
2 In the Column Name drop- down list, select the parameter to set.
3 In the Operator drop- down list, select the appropriate operator.
4 In the text box on the right, select the value with which to compare the
value of the Column Name parameter.
5 Click Add.
6 In the Query Name area, type a name for the query.
7 Click Save.
You can now use the query to develop thresholds for metrics or to define
a Quality chart. You can run the query, and export and save the results.
You can also rename and delete queries.
18 QC Chart Tool
Building Queries, Metric Sets, and Charts to Evaluate Extractions 2
See Also “To edit a query” on page 20
“To run a query” on page 21
“To delete a query” on page 21
“To rename a query” on page 21
“To import a query result” on page 22
“To export a query result” on page 22
“Query Builder dialog box” on page 66
To create a composite query
1 Create a basic query as described in “To create a query” on page 18.
2 Click AND or OR.
Use AND to find extractions that meet all criteria. Use OR to find
extractions that meet at least one criterion.
3 Create the next basic query.
4 To group composite queries, click a query, then click “(” or “)”. Repeat
for the query at the other end of the group.
5 In the Query Name area, enter a name for the query. See Figure 4 on
page 20.
6 Click Save.
To create a composite query
These components and attributes are described in “Query Builder dialog
box” on page 66.
Figure 4 shows an example of a query that finds all 1- color gene
expression extractions.
QC Chart Tool 19
2 Building Queries, Metric Sets, and Charts to Evaluate Extractions
To edit a query
Figure 4 Query Builder showing a composite query.
To edit a query
1 In the Navigator, under Queries in the Extractions pane, select the
query to edit.
2 On the command ribbon, click Queries and then click Edit.
Alternatively, right click on the query of interest and select Edit Query.
3 In the Query Builder dialog box, make any necessary changes. Click
Clear to remove all query conditions.
4 Click Save to save the query with the existing name.
OR
Click Save As to type a new name for the query and save it.
20 QC Chart Tool
To run a query
NOTE
1 In the Navigator, under Queries in the Extractions pane, select the
query to run.
2 On the command ribbon, click Queries and then click Run.
Alternatively, right click on the query of interest and select Run Query.
To delete a query
1 In the Navigator, under Queries in the Extractions pane, select the
query to delete.
2 On the command ribbon, click Queries and then click Delete.
Alternatively, right click on the query of interest and select Delete
Query.
3 In the Delete Query dialog box, click Yes to confirm the deletion.
If a query is used in a chart, you cannot delete the query.
Building Queries, Metric Sets, and Charts to Evaluate Extractions 2
To run a query
To rename a query
1 In the Navigator, under Queries in the Extractions pane, select the
query to rename.
2 On the command ribbon, click Queries and then click Rename.
Alternatively, right click on the query of interest and select Rename
Query.
3 In the Enter New Name dialog box, type the new name for the query.
4 Click OK.
QC Chart Tool 21
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