Processing imaging data from high throughput compound screen with EBImage
3
0
Entering edit mode
phil.chapman ▴ 150
@philchapman-8324
Last seen 4.8 years ago
United Kingdom

Hi,

My group are planning to conduct a 15k compound high content biology screen and I'm looking into options for analysing the image data.  We'd probably just be doing a simple cell count and maybe cell size to start with.  Although we have commerical software to do this (Definiens), I'm not sure how well our set-up will scale given the hardware it's on.  Another option is to use our institute's NGS compute cluster, and analyse the data using the Bioconductor package EBImage which I think would scale much better.

In terms of learning resources there's the package vignette and the following tutorial from CSAMA2015, but are there any additional workflow papers or other resources that might be helpful to me in setting this up?

http://www.bioconductor.org/help/course-materials/2015/BioC2015/BioC2015Oles.html

Thanks,

Phil

 

ebimage • 949 views
ADD COMMENT
4
Entering edit mode
@wolfgang-huber-3550
Last seen 4 days ago
EMBL European Molecular Biology Laborat…

Hi Phil

It's a good idea to do this with EBImage. We've used it for several imaging-based HT screens. The vignette of the paper  "A Map of Directional Genetic Interactions in a Metazoan Cell" by Bernd Fischer et al. generates all figures in the paper. It has a section on the HT image processing per se (as well as the downstream QA/QC, dimension reduction etc.): http://bioconductor.org/packages/release/data/experiment/html/DmelSGI.html

There is also a draft version of a teaching chapter on image data analysis that heavily relies on EBImage, and which I am happy to share (caveat - it's really a draft, forgive the bumps): http://www.huber.embl.de/users/whuber/.useR-book/Draft-Image-Analysis.pdf

Let us know about your experiences or questions that come up. Pull requests or suggestions are also welcome. It would also be interesting to hear what others on this forum use? E.g. there is also http://www.cellcognition.org/ (focus on time lapse imaging; interoperable with R through the cellh5 data exchange format (HDF5-based, http://www.cellh5.org ), and http://ilastik.org/ uses a clever interactive learning approach that maybe helpful if the segmentation is difficult.

Wolfgang

 

ADD COMMENT
0
Entering edit mode

Thanks Wolfgang this is exactly the sort of information I was hoping for.

My main issue to start with is how to get the image data out of the commercial software (Perkin Elmer Opera Phenix) in the first place and into an open format.  I naively assumed it would just be a bunch of images but it seems not.  The Open Microscopy Environment project seems to have lots of useful tools as well though so I'm hopeful I'll be able to work my way through this.

ADD REPLY
1
Entering edit mode

In that case RBioFormats might prove helpful. It provides an R interface to the OME image formats reader, which should allow you to load the data directly into R without the need of intermediate format conversion.

ADD REPLY
2
Entering edit mode
Andrzej Oleś ▴ 750
@andrzej-oles-5540
Last seen 8 months ago
Heidelberg, Germany

Dear Phil,

you can also have a look at the supplemental data packages accompanying the following papers. Each of these packages' vignette contains a description of the image analysis pipeline.

Cheers,
Andrzej

 

 

ADD COMMENT
0
Entering edit mode

This is great thanks Andrzej!

ADD REPLY
0
Entering edit mode
phil.chapman ▴ 150
@philchapman-8324
Last seen 4.8 years ago
United Kingdom

Some other useful links for posterity:

Earl Glynn's RNotes blog: http://earlglynn.github.io/RNotes/package/EBImage/index.html

Slideset from Wolfgang Huber: http://mlpm.eu/static/media/uploads/mlpm13_slides_huber01.pdf

Machine Learning in cell biology - teaching computers to read phenotypes: http://jcs.biologists.org/content/joces/126/24/5529.full.pdf

 

 

 

ADD COMMENT

Login before adding your answer.

Traffic: 538 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6