Using Cell-ID 1.4 with R for microscope-based cytometry.

This unit describes a method for quantifying various cellular parameters (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes r...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Chernomoretz, A., Bush, A., Yu, R., Gordon, A., Colman-Lerner, A.
Formato: JOUR
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19343647_vChapter14_n_p_Chernomoretz
Aporte de:
id todo:paper_19343647_vChapter14_n_p_Chernomoretz
record_format dspace
spelling todo:paper_19343647_vChapter14_n_p_Chernomoretz2023-10-03T16:36:14Z Using Cell-ID 1.4 with R for microscope-based cytometry. Chernomoretz, A. Bush, A. Yu, R. Gordon, A. Colman-Lerner, A. animal article cell computer program confocal microscopy cytology fluorescence microscopy human image processing instrumentation methodology statistical analysis yeast Animals Cells Data Interpretation, Statistical Humans Image Processing, Computer-Assisted Microscopy, Confocal Microscopy, Fluorescence Software Yeasts This unit describes a method for quantifying various cellular parameters (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell-ID (Gordon et al., 2007) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package tailored to analyze Cell-ID output. Both programs are open-source software packages. Copyright 2008 by John Wiley & Sons, Inc. Fil:Chernomoretz, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Bush, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Colman-Lerner, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_19343647_vChapter14_n_p_Chernomoretz
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic animal
article
cell
computer program
confocal microscopy
cytology
fluorescence microscopy
human
image processing
instrumentation
methodology
statistical analysis
yeast
Animals
Cells
Data Interpretation, Statistical
Humans
Image Processing, Computer-Assisted
Microscopy, Confocal
Microscopy, Fluorescence
Software
Yeasts
spellingShingle animal
article
cell
computer program
confocal microscopy
cytology
fluorescence microscopy
human
image processing
instrumentation
methodology
statistical analysis
yeast
Animals
Cells
Data Interpretation, Statistical
Humans
Image Processing, Computer-Assisted
Microscopy, Confocal
Microscopy, Fluorescence
Software
Yeasts
Chernomoretz, A.
Bush, A.
Yu, R.
Gordon, A.
Colman-Lerner, A.
Using Cell-ID 1.4 with R for microscope-based cytometry.
topic_facet animal
article
cell
computer program
confocal microscopy
cytology
fluorescence microscopy
human
image processing
instrumentation
methodology
statistical analysis
yeast
Animals
Cells
Data Interpretation, Statistical
Humans
Image Processing, Computer-Assisted
Microscopy, Confocal
Microscopy, Fluorescence
Software
Yeasts
description This unit describes a method for quantifying various cellular parameters (e.g., volume, total and subcellular fluorescence localization) from sets of microscope images of individual cells. It includes procedures for tracking cells over time. One purposefully defocused transmission image (sometimes referred to as bright-field or BF) is acquired to locate each cell. Fluorescent images (one for each of the color channels to be analyzed) are then acquired by conventional wide-field epifluorescence or confocal microscopy. This method uses the image processing capabilities of Cell-ID (Gordon et al., 2007) and data analysis by the statistical programming framework R (R-Development-Team, 2008), which we have supplemented with a package tailored to analyze Cell-ID output. Both programs are open-source software packages. Copyright 2008 by John Wiley & Sons, Inc.
format JOUR
author Chernomoretz, A.
Bush, A.
Yu, R.
Gordon, A.
Colman-Lerner, A.
author_facet Chernomoretz, A.
Bush, A.
Yu, R.
Gordon, A.
Colman-Lerner, A.
author_sort Chernomoretz, A.
title Using Cell-ID 1.4 with R for microscope-based cytometry.
title_short Using Cell-ID 1.4 with R for microscope-based cytometry.
title_full Using Cell-ID 1.4 with R for microscope-based cytometry.
title_fullStr Using Cell-ID 1.4 with R for microscope-based cytometry.
title_full_unstemmed Using Cell-ID 1.4 with R for microscope-based cytometry.
title_sort using cell-id 1.4 with r for microscope-based cytometry.
url http://hdl.handle.net/20.500.12110/paper_19343647_vChapter14_n_p_Chernomoretz
work_keys_str_mv AT chernomoretza usingcellid14withrformicroscopebasedcytometry
AT busha usingcellid14withrformicroscopebasedcytometry
AT yur usingcellid14withrformicroscopebasedcytometry
AT gordona usingcellid14withrformicroscopebasedcytometry
AT colmanlernera usingcellid14withrformicroscopebasedcytometry
_version_ 1807316576834158592