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We developed PathActMarker, an R package for inferring pathway activity of complex diseases. The package integrates widely used normalization methods for gene expression data and provides pathway data from six sources. Meanwhile, eight state-of-the-art tools can be used to convert the high-dimensional gene expression data into a biologically interpretable low-dimensional pathway activity matrix, and extensive evaluations are also included to measure the performance of these tools. The package also contains functions to identify important pathways as biomarkers based on statistical and machine learning algorithms, and provides a set of functions for interpretation and analysis.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (Grant No. 62202383), Guangdong Basic and Applied Basic Research Foundation (No. 2024A1515012602), and the National Key Research and Development Program of China (No. 2022YFD1801200).
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Authors and Affiliations
School of Computer Science, Northwestern Polytechnical University, Xi’an, 710072, China
Xingyi Li, Jun Hao, Xingyu Liao & Xuequn Shang
Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518063, China
Xingyi Li & Junming Li
School of Software, Northwestern Polytechnical University, Xi’an, 710072, China
Zhelin Zhao & Junming Li
Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410083, China
Min Li
- Xingyi Li
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- Jun Hao
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- Junming Li
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- Xingyu Liao
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- Min Li
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- Xuequn Shang
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Correspondence toXingyu Liao,Min Li orXuequn Shang.
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Li, X., Hao, J., Zhao, Z.et al. PathActMarker: an R package for inferring pathway activity of complex diseases.Front. Comput. Sci.19, 193908 (2025). https://doi.org/10.1007/s11704-024-40420-y
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