Key concepts: Cells are grown in a 384-well plate and therefore a Plate is an important unit of data as all samples from a single plate will share some level of technical artifacts. Each Well within the plate contains a single perturbation (e.g. each well is given a different drug). Within each Well there are multiple fields of view acquired by the microscope which we generally call Sites. Each Site will have images acquired in a set of Channels - a channel is a specific light path within a microscope and, when combined with specific fluorescent labels on a sample, represents specific biology that we are observing.
Module overview: This CellProfiler pipeline loads a single site from every well and performs object identification to identify nuclei and cells. It is used to efficiently subsample across a plate worth of images so that the biologist can confirm that the segmentation parameters are producing quality results. It outputs the input image, rescaled for easy visibility, with object outlines overlaid on it.
This module takes as inputs:
load_data_with_illum.csv which passes file lists associated with metadata to CellProfilerassaydev.cppipe which is the pipeline file for CellProfiler that tells it what operations to perform- images
- illumination correction images (as output by cellprofiler_illuminationcorrection)
It produces the output of a single image/site used for visualization.
It should run CellProfiler headless with the following command:
# abstracted command
cellprofiler -c -r -p PATH_TO_PIPELINE/assaydev.cppipe -o PATH_TO_OUTPUT -d PATH_TO_DONE_FILE/cp.is.done --data-file=PATH_TO_LOAD_DATA/load_data_with_illum.csv -g Metadata_Plate=PLATE,Metadata_Well=WELL
# command with example values
cellprofiler -c -r -p /home/ubuntu/bucket/cpg0037-oasis/broad/workspace/pipelines/2025_04_14_OASIS_U2OS_Industry_Batch4/assaydev.cppipe -o /home/ubuntu/local_output/BR00147158-P05 -d /home/ubuntu/local_output/BR00147158-P05/cp.is.done --data-file=/home/ubuntu/bucket/cpg0037-oasis/broad/workspace/load_data_csv_orig/2025_04_14_OASIS_U2OS_Industry_Batch4/BR00147158/load_data_with_illum.csv -g Metadata_Plate=BR00147158,Metadata_Well=P05
Key concepts: Cells are grown in a 384-well plate and therefore a
Plateis an important unit of data as all samples from a single plate will share some level of technical artifacts. EachWellwithin the plate contains a single perturbation (e.g. each well is given a different drug). Within eachWellthere are multiple fields of view acquired by the microscope which we generally callSites. EachSitewill have images acquired in a set ofChannels - a channel is a specific light path within a microscope and, when combined with specific fluorescent labels on a sample, represents specific biology that we are observing.Module overview: This CellProfiler pipeline loads a single site from every well and performs object identification to identify nuclei and cells. It is used to efficiently subsample across a plate worth of images so that the biologist can confirm that the segmentation parameters are producing quality results. It outputs the input image, rescaled for easy visibility, with object outlines overlaid on it.
This module takes as inputs:
load_data_with_illum.csvwhich passes file lists associated with metadata to CellProfilerassaydev.cppipewhich is the pipeline file for CellProfiler that tells it what operations to performIt produces the output of a single image/site used for visualization.
It should run CellProfiler headless with the following command: