Change Details

Oli implemented a few extra features to JACoP via a refactoring of the original JACoP code. The repository is hosted on C4Science at rJACOPB. Romain has made a macro using this tool to manage a folder and remember parameters. {F3882437} Plugins › BIOP › Image Analysis › BIOP JACoP Based on [[ https://imagejdocu.tudor.lu/plugin/analysis/jacop_2.0/just_another_colocalization_plugin/start| JACoP ]] = Available methods/metrics = [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Pearson correlation coefficient ]] [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Mander's coefficient article ]] [[ https://imagej.net/_images/e/e2/Costes_etalColoc.pdf | Costes article ]] [[ https://imagej.net/_images/9/9e/LietAlColoc.pdf| Li article ]] = Input = - A multi-channel image ( no need to split into independent channels) - Define channels to use - Define Threshold, either using an [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] or a User manually fixed value. {F13395950, size = full} We recommend to use Automatic method. It will compensate for subtle changes in illumination (microscopes are not perfect), or in case of variable expression of Fluorescent Proteins, the intensity from one cell to another (it woul need ROIs that define each cell). Nevertheless, it might fail if your images are very heterogenous (number of cells, intensities range, areas of signal...) If you can't find any method that gives satisfying result, consider then using a fixed value, manually set. We urge you to have controls (mono stained samples, acquired the same way as the test ones, same number of channels ...) to asses your thresholds are above the signal one can oberve in an unstained sample. = Output = - Results Table - Output Image with Thresholded Mask, FLuorogram (optionnal), Random image (new feature in BIOP JACoP) = Some Functionnnalities = == Region of Interest (ROIs) == With many ROIs in the ROI manager (defining cells for exemple), you will get an analysis per ROI. - **Crop ROIs** , generates a cropped iamge for each ROI. == Z-stack == - **Consider Z slices Separately** , output a single Z-stack image **BUT** the analysis are performed on each individual slice. //We recommend starting your pilot experiment , with z-stack and asses if the result depends of doing the analysis on 2D or 3D image and continue your acquisition campaign accordingly// - **Set Auto Thresholds On Stack Histogram** , when using one of the [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] you can use the method on individual slice or on the entire stack. {F13395937, size = full} == Set Advanced Parameters == to set size of the fluorogram {F13395918} = Install= Please use [[ https://c4science.ch/w/bioimaging_and_optics_platform_biop/image-processing/imagej_tools/update-site/ | PTBIOP update site ]]

Oli implemented a few extra features to JACoP via a refactoring of the original JACoP code. The repository is hosted on C4Science at rJACOPB. Romain has made a macro using this tool to manage a folder and remember parameters. {F3882437} Plugins › BIOP › Image Analysis › BIOP JACoP Based on [[ https://imagejdocu.tudor.lu/plugin/analysis/jacop_2.0/just_another_colocalization_plugin/start| JACoP ]] = Available methods/metrics = [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Pearson correlation coefficient ]] [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Mander's coefficient article ]] [[ https://imagej.net/_images/e/e2/Costes_etalColoc.pdf | Costes article ]] [[ https://imagej.net/_images/9/9e/LietAlColoc.pdf| Li article ]] = Input = - A multi-channel image ( no need to split into independent channels) - Define channels to use - Define Threshold, either using an [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] or a User manually fixed value. {F13395950, size = full} //We recommend to use Automatic method. It will compensate for subtle changes in illumination (microscopes are not perfect), or in case of variable expression of Fluorescent Proteins, the intensity from one cell to another (it woul need ROIs that define each cell). Nevertheless, it might fail if your images are very heterogenous (number of cells, intensities range, areas of signal...) If you can't find any method that gives satisfying result, consider then using a fixed value, manually set. // (IMPORTANT) We urge you to have controls (mono stained samples, acquired the same way as the test ones, same number of channels ...) to verify that the defined thresholds are above the signal one can observe in an unstained sample. You will always have some crosstalk/bleedthrough, always! = Output = - Results Table - Output Image with Thresholded Mask, FLuorogram (optionnal), Random image (new feature in BIOP JACoP) {F13396006, size = full} = Some Functionnnalities = == Region of Interest (ROIs) == With many ROIs in the ROI manager (defining cells for exemple), you will get an analysis per ROI. - **Crop ROIs** , generates a cropped iamge for each ROI. == Z-stack == - **Consider Z slices Separately** , output a single Z-stack image **BUT** the analysis are performed on each individual slice. //We recommend starting your pilot experiment , with z-stack and asses if the result depends of doing the analysis on 2D or 3D image and continue your acquisition campaign accordingly// - **Set Auto Thresholds On Stack Histogram** , when using one of the [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] you can use the method on individual slice or on the entire stack. {F13395937, size = full} == Set Advanced Parameters == to set size of the fluorogram {F13395918} = Install= Please use [[ https://c4science.ch/w/bioimaging_and_optics_platform_biop/image-processing/imagej_tools/update-site/ | PTBIOP update site ]]

Oli implemented a few extra features to JACoP via a refactoring of the original JACoP code. The repository is hosted on C4Science at rJACOPB. Romain has made a macro using this tool to manage a folder and remember parameters. {F3882437} Plugins › BIOP › Image Analysis › BIOP JACoP Based on [[ https://imagejdocu.tudor.lu/plugin/analysis/jacop_2.0/just_another_colocalization_plugin/start| JACoP ]] = Available methods/metrics = [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Pearson correlation coefficient ]] [[ https://en.wikipedia.org/wiki/Pearson_correlation_coefficient | Mander's coefficient article ]] [[ https://imagej.net/_images/e/e2/Costes_etalColoc.pdf | Costes article ]] [[ https://imagej.net/_images/9/9e/LietAlColoc.pdf| Li article ]] = Input = - A multi-channel image ( no need to split into independent channels) - Define channels to use - Define Threshold, either using an [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] or a User manually fixed value. {F13395950, size = full} //We recommend to use Automatic method. It will compensate for subtle changes in illumination (microscopes are not perfect), or in case of variable expression of Fluorescent Proteins, the intensity from one cell to another (it woul need ROIs that define each cell). Nevertheless, it might fail if your images are very heterogenous (number of cells, intensities range, areas of signal...) If you can't find any method that gives satisfying result, consider then using a fixed value, manually set. // (IMPORTANT) We urge you to have controls (mono stained samples, acquired the same way as the test ones, same number of channels ...) to asses yourto verify that the defined thresholds are above the signal one can obobserve in an unstained sample. You will always have some crosstalk/bleedthrough, always! = Output = - Results Table - Output Image with Thresholded Mask, FLuorogram (optionnal), Random image (new feature in BIOP JACoP) {F13396006, size = full} = Some Functionnnalities = == Region of Interest (ROIs) == With many ROIs in the ROI manager (defining cells for exemple), you will get an analysis per ROI. - **Crop ROIs** , generates a cropped iamge for each ROI. == Z-stack == - **Consider Z slices Separately** , output a single Z-stack image **BUT** the analysis are performed on each individual slice. //We recommend starting your pilot experiment , with z-stack and asses if the result depends of doing the analysis on 2D or 3D image and continue your acquisition campaign accordingly// - **Set Auto Thresholds On Stack Histogram** , when using one of the [[ https://imagej.net/Auto_Threshold | Automatic Thresholding Method ]] you can use the method on individual slice or on the entire stack. {F13395937, size = full} == Set Advanced Parameters == to set size of the fluorogram {F13395918} = Install= Please use [[ https://c4science.ch/w/bioimaging_and_optics_platform_biop/image-processing/imagej_tools/update-site/ | PTBIOP update site ]]