Imaging

Image analysis using Galaxy

Requirements

Before diving into this topic, we recommend you to have a look at:

Material

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides () and tutorial () buttons below.

Introduction

Start here if you are new to Image Analysis in Galaxy

Lesson Slides Hands-on Recordings Input dataset Workflows
Introduction to Image Analysis using Galaxy
Image segmentation Image thresholding Conversion Object counting Overlay Fluorescence microscopy
Overview of the Galaxy OMERO-suite - Upload images and metadata in OMERO using Galaxy
Data management Data handling Data sharing ROI selection
FAIR Bioimage Metadata
Data management Metadata Bioimaging
REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data
Data management Metadata Bioimaging

Analyses

These tutorials will help you analyse your image data

Lesson Slides Hands-on Recordings Input dataset Workflows
Analyse HeLa fluorescence siRNA screen
Image segmentation Object feature extraction Image thresholding High-throughput screening Overlay Fluorescence microscopy
End-to-End Tissue Microarray Image Analysis with Galaxy-ME
Image segmentation Tissue imaging
Nucleoli segmentation and feature extraction using CellProfiler
Image segmentation Object feature extraction Multi-channel image
Object tracking using CellProfiler
Isolated object tracking Multi-channel image
Quantification of electrophoresis gel bands using QuPath and Galaxy imaging tools
ROI selection Conversion Object feature extraction Multi-channel image
Quantification of single-molecule RNA fluorescence in situ hybridization (smFISH) in yeast cell lines
IDR dataset Spot detection Rasterisation Overlay
Tracking of mitochondria and capturing mitoflashes
Isolated object tracking Temporal analysis Time-lapse data
Using BioImage.IO models for image analysis in Galaxy
Image segmentation Image annotation Deep learning
Voronoi segmentation
Tessellation Image segmentation Object counting Overlay Multi-channel image

Advanced topics

Tutorials covering advanced topics

Lesson Slides Hands-on Recordings Input dataset Workflows
Execute a BiaPy workflow in Galaxy
Image segmentation Image annotation Deep learning Conversion Overlay 3D image Volume rendering
Parameter tuning and optimization - Evaluating nuclei segmentation with Galaxy
Image segmentation Parameter optimisation Validation
Training Custom YOLO Models for Segmentation of Bioimages
Image segmentation Image annotation Deep learning

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Editorial Board

This material is reviewed by our Editorial Board:

orcid logoLeonid Kostrykin avatar Leonid Kostrykinorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-Solano

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Contributors

This material was contributed to by:

Daniel Franco Barranco avatar Daniel Franco Barrancoorcid logoArmin Dadras avatar Armin Dadrasorcid logoAnne Fouilloux avatar Anne FouillouxReyhaneh Tavakoli avatar Reyhaneh Tavakoliorcid logoBjörn Grüning avatar Björn Grüningorcid logoLeonid Kostrykin avatar Leonid Kostrykinorcid logoHelena Rasche avatar Helena Rascheorcid logoRiccardo Massei avatar Riccardo Masseiorcid logoEven Moa Myklebust avatar Even Moa Myklebustorcid logoThomas Wollmann avatar Thomas Wollmannorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoKhaled Jum'ah avatar Khaled Jum'ahorcid logoDiana Chiang Jurado avatar Diana Chiang JuradoArif ul Maula Khan avatar Arif ul Maula Khanorcid logoMartin Čech avatar Martin ČechAnup Kumar avatar Anup Kumarorcid logoJulia Jakiela avatar Julia JakielaYi Sun avatar Yi Sunorcid logoCameron Watson avatar Cameron Watsonorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-SolanoLaura Cooper avatar Laura Cooperorcid logoKrzysztof Poterlowicz avatar Krzysztof PoterlowiczJean-Karim Hériché avatar Jean-Karim Hérichéorcid logoCristóbal Gallardo avatar Cristóbal Gallardoorcid logoPaul De Geest avatar Paul De Geestorcid logoAllison Creason avatar Allison Creasonorcid logoKatarzyna Kamieniecka avatar Katarzyna Kamieniecka

Funding

These individuals or organisations provided funding support for the development of this resource

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UFR
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DFG
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OSCARS
The OSCARS project has received funding from the European Commission’s Horizon Europe Research and Innovation programme under grant agreement No. 101129751
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ELIXIR Europe
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OSCARS-FIESTA
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NFDI4Bioimage
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de.NBI
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DASH UK
This Fellowship was funded through the ELIXIR-UK DaSH project as part of the UKRI Innovation Scholars: Data Science Training in Health and Bioscience call (DaSH). (MR/V038966/1). The project aims to embed Research Data Management (RDM) know-how into UK universities and institutes by producing and delivering training in FAIR data stewardship using ELIXIR-UK knowledge and resources.

References