DPre

DPre quantifies per-gene transcriptional similarity between RNA-Seq datasets and reference cell type transcriptome libraries to identify destination cell types and directional differentiation biases in experiments involving growth factors, chemical inhibitors, or ectopic gene expression, including partially differentiated cells with indeterminate transcriptional identities.

Key Features:

• Transcriptional Similarity Scoring: DPre employs a per-gene transcriptional similarity scoring system to compare RNA-Seq experimental samples with reference cell type expression profiles.
• Directional Bias Identification: By comparing experimental data against extensive cell type transcriptome libraries, DPre reveals directional biases and potential trajectories in differentiation and cell conversion experiments.
• Visualization of Transcriptional Changes: DPre provides visualizations that highlight shifts in transcriptional identity and identify key genes responsible for those shifts.

Scientific Applications:

• Cell differentiation and conversion analysis: Assess transcriptional landscapes and biases in in vitro cell type conversion experiments.
• Regenerative medicine: Evaluate outcomes and differentiation biases relevant to protocol development for regenerative strategies.
• Developmental biology: Investigate trajectories and partial differentiation states during development.
• Disease modeling: Provide insights into genes driving cell type changes and biases in models of disease.

Methodology:

DPre aligns gene expression profiles from experimental RNA-Seq samples to comprehensive reference libraries or specific target expression profiles and computes per-gene transcriptional similarity scores that indicate resemblance to known cell types and directional differentiation bias.