General Knowledge

When To Say ‘Good Enough’

Beth Cimini

One of the most common questions I’m asked when helping a collaborator with an image analysis project is:

“How do I know when my analysis workflow is doing well enough at finding the objects or measuring the things I care about?”

Unfortunately, it’s also one of the hardest questions to answer!  In an ideal world, we’d be able to achieve perfect recognition and/or segmentation of our biological objects every time, and get out perfect data! Alas, biology is almost never so...

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Tricks for maintaining your CV/resume with Google Docs: easy to edit, immediately published

Jeanelle Ackerman

You’ve earned degrees, authored papers, mentored supervisees, and traveled far and wide to speak about your work… And ideally it’s nicely showcased in your resume or curriculum vitae (CV), all updated and ready to go. But, if you’re like most academics, your CV is a sorely outdated PDF and upon its request, you always find yourself scrambling to dig up recent accomplishments to prove you’ve not just been lounging around for the last 6 months (or years). And updating it requires locating an elusive latest version of a Word...

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Tracking projects with Gmail tags: Collaborating through email

Anne Carpenter

As the PI of the Carpenter lab (a.k.a. Broad Institute Imaging Platform, including the CellProfiler team), people often ask how I manage so many ongoing collaborations: we discuss 50+ external projects each year so it is a lot to track! I am happy to reveal our secrets.

The goal


First, let me describe the problem we are trying to solve: we need a way/place to post project updates, raw data, and emails about a given project, so everyone in the lab can have access to info (most...

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Help! Why do my output images seem all black?

Beth Cimini

Double clicking on the output images produced by CellProfiler sometimes opens up a screen in your operating system’s default image viewer that looks all black. This can make it seem like your pipeline didn’t work or didn’t produce the right output. However, this can happen for a couple of reasons:

(a) If you’re exporting objects and have only a few objects in your image
(b) If you’re exporting 16-bit images

This has to do with the fact that most non-scientific photo software is designed to show 256 levels...

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Be a histology hero with CellProfiler

Minh Doan

Thanks to the rapid advancement in image processing, we now have so many techniques to characterize cellular and subcellular objects (hooray CellProfiler!) Measuring cultured cells in monolayers is (usually) easy…but what about examining how cells interact with each other and their surroundings? Such experiments are often conducted using highly confluent cell cultures, tissue sections, or densely cell-packed organoids. At this level, clusters of cells gather, tightly bind and overlap to form cell niches, and often in a single area...

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Help! Why does CellProfiler say it can’t find any valid image sets?

Beth Cimini

Defining the input to CellProfiler can be the hardest part of getting your pipeline set up and your analysis underway.  Incoming images are configured in the first 4 modules of CellProfiler – Images, Metadata, NamesAndTypes, and Groups – which offer lots of flexibility. But it’s sometimes confusing what each one does, and it’s not always obvious which ones you need for your experiment.

If you have mistakes in any of these modules, you may run across the dreaded errors ‘The pipeline did not identify any...

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Help! What are these three different modules to identify objects?

Beth Cimini

It can be confusing when you’re trying to set up your first pipeline to figure out which modules to use to generate your objects!  A helpful way to understand the difference between Identifying Primary, Secondary, and Tertiary objects:

  • Primary objects are segmented independently from any other object you’ve designated (like segmenting nuclei from your DAPI channel).
  • Secondary objects are created around a primary object, and so they usually need two pieces of information – a primary...
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Looking for the Unexpected: Unbiased Image Analysis

Anne Carpenter

So you already know how to put together an image analysis pipeline to measure particular phenotypes of interest? Great!

Have you ever considered looking for the unexpected? Say you are comparing two treatment conditions, such as a negative control vs. a hormone treatment. You may have in mind phenotypes to measure, so you use CellProfiler to accurately The
...

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