3. Working with rectangular array of samples

In compound screening projects by MALDI-MS, sample droplets are often dispensed into M by N rectangular array. Matching sample name to each droplet in the array is a necessary task for screening. macroMS provides a function for matching sample name to sample array.

Matching identity by array registration

When all spots in the array are recognized by macroMS, macroMS can perform array registration which is obtaining row position and column position of each spot in the array. User can input a CSV file containing M-by-N array of sample names, and macroMS will use column position and row position to match file name for each sample.

First, an example image for a 51 X 51 array is thresholded:

Next, feature recognition is performed to find all the spots in the array. Threshold parameter should be optimized to find all spots by image analysis, without manually adding targets.

Next, four corner edges of the array should be indicated to macroMS. First click 'Rectangular sample array' then click 'Mark corners.' Click on all four of the corner edge spots of the array, resulting in green solid boxes on the four spots. Alternatively, the corner edge target spot can be removed by 'Box remove' function and the corner edge mark can be added by clicking in 'Mark corners' mode.

Number of columns and rows should be indicated, and clicking 'Register array' button starts the array registration operation. When finished, the results of array registration should be inspected to confirm the registration. First, clicking 'Plot registration' shows each column as a yellow line and each row as a red line. All of the red and yellow lines should be straight.

Second, clicking 'Check error' shows maps of registration error per each spot in the array. Low values within +/- 10 throughout the map indicates the registration was successful.

After confirming with the registration results, the user uploads a text file containing M-by-N array of sample names. This array can be created in an Excel spreadsheet like below and should be saved as a tab-deliminated text file from Excel by using the 'save as' function. The example name matrix is shown below.

The column position and the row position of the cell within the name matrix defines which spot the name corresponds to, like below. Therefore, the number of rows and columns in the name matrix should be equal to that of the spot array.

There is a max character limit for sample name which is 27. Any character that is not alphanumeric (characters other than a-z,A-Z,0-9) will be converted to underscore including whitespaces. Font size should be inputted for display purpose, and low font size 1~3 is recommended. The sample name can be uploaded by 'Load names' button.

After uploading the sample name file, sample names are displayed on the viewer for the user to confirm.

Then, target geometry file can be generated normally, as described in Section 2. The data analysis results will show the sample names matched for each spot, as below.

If sample names are not loaded for the registered array, the above table will list the row number and the column number of the spot within the array.

Creating an array without image analysis

Alternatively, when the sample spots are difficult to be detected by image analysis, an arbitrary array can be added without image analysis. For example, target array can be added to the image below.

First click 'Rectangular sample array' then click 'Mark corners.' Click the four corner spots of the array as shown below. Input the number of rows and columns for the array. The max limit for column value and row value is 50.

Then click 'Add array.' The added target array is shown below.

The CSV file for sample names can be uploaded to insert sample names per each spot. Note that added array can have less accuracy compared to array registration as shown below. Therefore, this functionality is recommended for larger samples.

Proceed to generating geometry file for MALDI-MS analysis.

Resolving missing spots

The total number of samples may not equal to the number defined by the array. For example, there can be 1521 samples for a 1536 array (32X48). In this case, after feature recognition finding 1521, the remaining 15 target boxes should be manually added to the missing spots by the Edit blobs mode. After achieving 1536, array registration can proceed normally followed by loading names. The name array should be 1536 (32X48), and there should be a filler word for the 15 manually added spots such as 'Null' or 'N/A'. After loading names, the manually added targets can be dropped by 'Edit blobs' mode. The same method applies for created arrays also, and the corner mark should be located at the estimated location for the missing corner spot.

Note for using the corner edge spots as fiducial

The droplets / samples at the four corner edges of the rectangular spot array can be fiducials. After registering the array, switch to fiducial edit mode, and clicking the corner spots will add fiducial box around the clicked blob. The two concentric boxes indicate the spot is both target and fiducial point. Note that if there is any fiducial point that is located within any target box ('Blobs'), the fiducial points will appear at the last in the dropdown menu for the Teach Positions window of the instrument control software. The reason is because there is no automatic mechanism within the instrument software for separating fiducials from target list for this particular case. This means the corner spots will be sampled twice, one for target and one for fiducial. Placing the fiducials at the last in the target order enables acquiring data for target first.

Warning against creating a dense array over single pixel area

macroMS is not built for handling arrays spanning over a single pixel or less. In this case, the following information becomes invalid: row and column position number for each spot as well as sample names. The MS data and the coordinate information for each spot remain valid.

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