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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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timeClip: pathway analysis for time course data without replicates.

Paolo Martini, Gabriele Sales, Enrica Calura

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    |August 1, 2014
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    Summary
    This summary is machine-generated.

    TimeClip is a new pathway analysis tool for time-course gene expression data lacking replicates. It identifies and highlights time-dependent pathways, revealing biological process timing, such as in muscle regeneration.

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    Area of Science:

    • Bioinformatics
    • Systems Biology
    • Genomics

    Background:

    • Time-course gene expression experiments track biological processes over time.
    • Replication in long time-series experiments is often limited due to cost.
    • Existing pathway analysis methods do not address temporal variations in time-course data.

    Purpose of the Study:

    • To develop a novel topology-based pathway analysis method for time-course gene expression data without replicates.
    • To identify and dissect time-dependent pathways and their dynamic components.
    • To apply the method to understand the temporal dynamics of biological processes like muscle regeneration.

    Main Methods:

    • timeClip combines dimension reduction and graph decomposition techniques.
    • It first selects time-dependent pathways and then highlights the most dynamic portions.
    • The method was validated using simulated data and a mouse muscle regeneration dataset.

    Main Results:

    • timeClip effectively identifies time-dependent pathways in simulated data across various settings.
    • Analysis of mouse muscle regeneration data revealed 76 time-dependent pathways, many linked to regeneration.
    • The 'mTOR signaling pathway' dynamics were detailed, illustrating early activation to late protein production.

    Conclusions:

    • timeClip offers a significant advancement in analyzing time-dependent biological pathways.
    • The method successfully isolates and dissects pathways with temporal components.
    • It accurately characterized the timing of muscle fiber regeneration processes.