Back

SImBA-SiQuAl: a new tool enabling high-content high-throughput phenotypic profiling of 3D microtumours.

Van De Vijver, E.; Dewitte, K.; Van Alboom, A.; Christophe, A.; Van Vlierberghe, H.; Van Troys, M.

2026-04-16 cancer biology
10.64898/2026.04.14.718366 bioRxiv
Show abstract

Three-dimensional microtumour models such as spheroids are increasingly used in cancer research as they better capture tumour architecture, growth and invasion than conventional two-dimensional cultures. However, robust and accessible tools for quantitative analysis remain limited. Here we present SImBA-SiQuAl, an integrated open-source workflow for high-throughput quantitative phenotyping of 3D spheroids and organoids. The pipeline combines SImBA, an automated image-analysis framework for performant quality-controlled image segmentation and multi-feature extraction from spheroid assays, with SiQuAl, a downstream analysis platform that automatically performs comprehensive statistical and multivariate analyses to reveal phenotypic differences between experimental conditions. In a first case study, SImBA-SiQuAl resolves intrinsic invasion phenotypes between cancer cell lines. In a second case study, the workflow quantifies both uniform and heterogeneous responses in a spheroid drug screening assay. Together, SImBA-SiQuAl provides a new, timely tool for high-throughput, high-content microtumour phenomics in cancer research. MOTIVATION3D-microtumour assays such as spheroids and organoids are increasingly used in preclinical research. These assays generate rich phenotypic imaging data, but quantitative automated analysis remains a major bottleneck. This limits reproducibility, scalability, and broad adoption for large-scale, high-content phenomics studies, but also implies biologically relevant phenotypic (heterogeneous) responses in e.g. perturbation studies may not be comprehensively addressed. SImBA-SiQuAl is developed to address this gap by providing an open-source, integrated workflow offering solutions in both the image processing and downstream analysis. Together, this enables in-depth quantitative analysis of 3D microtumour phenotypes across experimental settings. HIGHLIGHTSO_LISImBA-SiQuAl provides a complete end-to-end workflow for high-throughput, high-content, quantitative 3D microtumour analysis, from quality-controlled image segmentation to statistical, multivariate and cluster-based biological interpretation. C_LIO_LISImBA-SiQuAl is broadly applicable across multiple 3D systems and assay types. C_LIO_LIWe demonstrate the workflow can capture biologically meaningful heterogeneity and treatment response at scale, supporting robust and unbiased analysis. C_LIO_LIBy combining accessibility, flexibility and analytical depth, SImBA-SiQuAl addresses a key unmet need for accessible advanced open-source tools in 3D preclinical research. C_LI

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
1633 papers in training set
Top 6%
6.2%
2
Scientific Reports
3102 papers in training set
Top 20%
6.2%
3
Cell Reports Methods
141 papers in training set
Top 0.4%
6.2%
4
Biological Imaging
15 papers in training set
Top 0.1%
6.2%
5
Bioinformatics
1061 papers in training set
Top 4%
6.2%
6
Patterns
70 papers in training set
Top 0.1%
4.8%
7
PLOS ONE
4510 papers in training set
Top 32%
4.8%
8
Computational and Structural Biotechnology Journal
216 papers in training set
Top 1%
3.9%
9
npj Systems Biology and Applications
99 papers in training set
Top 0.5%
3.6%
10
npj Digital Medicine
97 papers in training set
Top 1%
3.5%
50% of probability mass above
11
Journal of Microscopy
18 papers in training set
Top 0.1%
3.2%
12
iScience
1063 papers in training set
Top 8%
2.7%
13
Bioinformatics Advances
184 papers in training set
Top 2%
2.6%
14
Nature Communications
4913 papers in training set
Top 45%
2.6%
15
Communications Biology
886 papers in training set
Top 4%
2.4%
16
Genome Medicine
154 papers in training set
Top 5%
1.7%
17
Disease Models & Mechanisms
119 papers in training set
Top 1%
1.7%
18
Scientific Data
174 papers in training set
Top 1%
1.7%
19
GigaScience
172 papers in training set
Top 2%
1.6%
20
BMC Bioinformatics
383 papers in training set
Top 5%
1.6%
21
Journal of Translational Medicine
46 papers in training set
Top 2%
1.2%
22
SLAS Discovery
25 papers in training set
Top 0.1%
1.2%
23
Nucleic Acids Research
1128 papers in training set
Top 15%
0.9%
24
Biology Methods and Protocols
53 papers in training set
Top 2%
0.9%
25
Frontiers in Bioinformatics
45 papers in training set
Top 0.7%
0.9%
26
Cancer Research
116 papers in training set
Top 4%
0.7%
27
Briefings in Bioinformatics
326 papers in training set
Top 7%
0.7%
28
Nature Biotechnology
147 papers in training set
Top 8%
0.7%
29
Physics in Medicine & Biology
17 papers in training set
Top 0.5%
0.7%
30
Nature Methods
336 papers in training set
Top 6%
0.7%