InPheRNo-ChIP

InPheRNo-ChIP integrates RNA-seq, transcription factor (TF)-specific ChIP-seq, and phenotypic labels to reconstruct phenotype-relevant gene regulatory networks associated with endoderm development.

Key Features:

• Phenotype-aware GRN inference: Directly incorporates phenotypic information during network inference to distinguish lineage-specific from general regulatory interactions, unlike phenotype-agnostic methods.
• Multimodal data integration: Combines RNA-seq, TF-specific ChIP-seq, and phenotypic labels in a unified framework.
• Probabilistic graphical model: Models the simultaneous effect of TFs on their putative target genes to influence a particular phenotypic outcome.
• Benchmarking capability: Identifies regulatory interactions involving endoderm markers FOXA2, SMAD2, and SOX17, outperforming other methods when validated against scRNA-seq CRISPRi data.
• Ablation analysis: Enables assessment of the synergistic contribution of ChIP-seq, RNA-seq, and phenotypic data to network reconstruction accuracy.

Scientific Applications:

• Endoderm development: Infers the gene regulatory network governing differentiation of human embryonic stem cells into definitive endoderm.
• Early human embryogenesis: Deciphers lineage-relevant gene regulatory networks during endoderm formation to understand developmental mechanisms.
• Lineage-specific interaction identification: Distinguishes lineage-specific regulatory interactions from general regulatory interactions through phenotype incorporation.

Methodology:

The core method is a probabilistic graphical model that models the simultaneous effect of transcription factors on their putative target genes to influence a particular phenotypic outcome.