-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathGFPmCherry_STARmap_TotalIntensityRatio.cppipe
208 lines (197 loc) · 11 KB
/
GFPmCherry_STARmap_TotalIntensityRatio.cppipe
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
CellProfiler Pipeline: http://www.cellprofiler.org
Version:5
DateRevision:407
GitHash:
ModuleCount:11
HasImagePlaneDetails:False
Images:[module_num:1|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
:
Filter images?:Images only
Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "[\\\\\\\\/]\\\\.")
Metadata:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Extract metadata?:Yes
Metadata data type:Text
Metadata types:{}
Extraction method count:1
Metadata extraction method:Extract from file/folder names
Metadata source:File name
Regular expression to extract from file name:^(?P<Time>.*)_(?P<Date>.*)_(?P<Stack>.*)_ch(?P<ChannelNumber>[0-9]{1,2})
Regular expression to extract from folder name:(?P<Date>[0-9]{4}_[0-9]{2}_[0-9]{2})$
Extract metadata from:All images
Select the filtering criteria:and (file does contain "")
Metadata file location:Default Input Folder sub-folder|
Match file and image metadata:[]
Use case insensitive matching?:No
Metadata file name:
Does cached metadata exist?:No
NamesAndTypes:[module_num:3|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Assign a name to:Images matching rules
Select the image type:Grayscale image
Name to assign these images:DNA
Match metadata:[{'GFP': 'Date', 'Hoechst': 'Date', 'mCherry': 'Date'}]
Image set matching method:Metadata
Set intensity range from:Image metadata
Assignments count:3
Single images count:0
Maximum intensity:255.0
Process as 3D?:No
Relative pixel spacing in X:1.0
Relative pixel spacing in Y:1.0
Relative pixel spacing in Z:1.0
Select the rule criteria:and (file does contain "ch00")
Name to assign these images:Hoechst
Name to assign these objects:Cell
Select the image type:Grayscale image
Set intensity range from:Image metadata
Maximum intensity:255.0
Select the rule criteria:and (file does contain "ch01")
Name to assign these images:GFP
Name to assign these objects:Nucleus
Select the image type:Grayscale image
Set intensity range from:Image metadata
Maximum intensity:255.0
Select the rule criteria:and (file does contain "ch02")
Name to assign these images:mCherry
Name to assign these objects:Cytoplasm
Select the image type:Grayscale image
Set intensity range from:Image metadata
Maximum intensity:255.0
Groups:[module_num:4|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Do you want to group your images?:No
grouping metadata count:1
Metadata category:Date
EnhanceOrSuppressFeatures:[module_num:5|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Use filtering to enhance the foci speckles in the image. The feature size setting should be specified to be at least as large as the largest feature to be enhanced. ']|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False]
Select the input image:mCherry
Name the output image:EnhancedmCherry
Select the operation:Enhance
Feature size:15
Feature type:Speckles
Range of hole sizes:1,10
Smoothing scale:2.0
Shear angle:0.0
Decay:0.95
Enhancement method:Tubeness
Speed and accuracy:Fast
Rescale result image:Yes
EnhanceOrSuppressFeatures:[module_num:6|svn_version:'Unknown'|variable_revision_number:7|show_window:False|notes:['Use filtering to enhance the foci speckles in the image. The feature size setting should be specified to be at least as large as the largest feature to be enhanced. ']|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False]
Select the input image:GFP
Name the output image:EnhancedGFP
Select the operation:Enhance
Feature size:15
Feature type:Speckles
Range of hole sizes:1,10
Smoothing scale:2.0
Shear angle:0.0
Decay:0.95
Enhancement method:Tubeness
Speed and accuracy:Fast
Rescale result image:Yes
IdentifyPrimaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Identify mCherry in both cytoplasm and vesicles.']|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False]
Select the input image:EnhancedmCherry
Name the primary objects to be identified:mCherryall
Typical diameter of objects, in pixel units (Min,Max):2,50
Discard objects outside the diameter range?:Yes
Discard objects touching the border of the image?:Yes
Method to distinguish clumped objects:Intensity
Method to draw dividing lines between clumped objects:Intensity
Size of smoothing filter:4
Suppress local maxima that are closer than this minimum allowed distance:4
Speed up by using lower-resolution image to find local maxima?:Yes
Fill holes in identified objects?:After both thresholding and declumping
Automatically calculate size of smoothing filter for declumping?:Yes
Automatically calculate minimum allowed distance between local maxima?:Yes
Handling of objects if excessive number of objects identified:Continue
Maximum number of objects:500
Display accepted local maxima?:No
Select maxima color:Blue
Use advanced settings?:Yes
Threshold setting version:12
Threshold strategy:Global
Thresholding method:Robust Background
Threshold smoothing scale:1.3488
Threshold correction factor:1.0
Lower and upper bounds on threshold:0.0,1.0
Manual threshold:0.0
Select the measurement to threshold with:None
Two-class or three-class thresholding?:Two classes
Log transform before thresholding?:No
Assign pixels in the middle intensity class to the foreground or the background?:Foreground
Size of adaptive window:50
Lower outlier fraction:0.05
Upper outlier fraction:0.00
Averaging method:Median
Variance method:Standard deviation
# of deviations:2.0
Thresholding method:Otsu
IdentifyPrimaryObjects:[module_num:8|svn_version:'Unknown'|variable_revision_number:14|show_window:False|notes:['Identify GFP in both cytoplasm and vesicles.']|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False]
Select the input image:EnhancedGFP
Name the primary objects to be identified:GFPall
Typical diameter of objects, in pixel units (Min,Max):2,50
Discard objects outside the diameter range?:Yes
Discard objects touching the border of the image?:Yes
Method to distinguish clumped objects:Intensity
Method to draw dividing lines between clumped objects:Intensity
Size of smoothing filter:4
Suppress local maxima that are closer than this minimum allowed distance:4
Speed up by using lower-resolution image to find local maxima?:Yes
Fill holes in identified objects?:After both thresholding and declumping
Automatically calculate size of smoothing filter for declumping?:Yes
Automatically calculate minimum allowed distance between local maxima?:Yes
Handling of objects if excessive number of objects identified:Continue
Maximum number of objects:500
Display accepted local maxima?:No
Select maxima color:Blue
Use advanced settings?:Yes
Threshold setting version:12
Threshold strategy:Global
Thresholding method:Robust Background
Threshold smoothing scale:1.3488
Threshold correction factor:1.0
Lower and upper bounds on threshold:0.0,1.0
Manual threshold:0.0
Select the measurement to threshold with:None
Two-class or three-class thresholding?:Two classes
Log transform before thresholding?:No
Assign pixels in the middle intensity class to the foreground or the background?:Foreground
Size of adaptive window:50
Lower outlier fraction:0.05
Upper outlier fraction:0.00
Averaging method:Median
Variance method:Standard deviation
# of deviations:2.0
Thresholding method:Otsu
MeasureImageIntensity:[module_num:9|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure mCherry intensity in cell.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select images to measure:mCherry
Measure the intensity only from areas enclosed by objects?:No
Select input object sets:
Calculate custom percentiles:No
Specify percentiles to measure:10,90
MeasureImageIntensity:[module_num:10|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Measure GFP intensity in cell.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select images to measure:GFP
Measure the intensity only from areas enclosed by objects?:No
Select input object sets:GFPall
Calculate custom percentiles:No
Specify percentiles to measure:10,90
ExportToSpreadsheet:[module_num:11|svn_version:'Unknown'|variable_revision_number:13|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
Select the column delimiter:Comma (",")
Add image metadata columns to your object data file?:Yes
Add image file and folder names to your object data file?:No
Select the measurements to export:No
Calculate the per-image mean values for object measurements?:No
Calculate the per-image median values for object measurements?:No
Calculate the per-image standard deviation values for object measurements?:No
Output file location:Elsewhere...|D:\\MIT\\STARmap\\STARmap_computation\\GFP-mCherry\\20210513_Neuron
Create a GenePattern GCT file?:No
Select source of sample row name:Metadata
Select the image to use as the identifier:None
Select the metadata to use as the identifier:None
Export all measurement types?:No
Press button to select measurements:
Representation of Nan/Inf:NaN
Add a prefix to file names?:No
Filename prefix:MyExpt_
Overwrite existing files without warning?:Yes
Data to export:Image
Combine these object measurements with those of the previous object?:No
File name:DATA.csv
Use the object name for the file name?:Yes