jlfan.bsky.social
PhD candidate in BME @Columbia | computational #cancer research at http://azizilab.com
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#Echidna is now publicly available at github.com/azizilab/ech..., and may also be installed on PyPI and Bioconda! We hope you will join us in understanding the role of CNAs in phenotypic plasticity!
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š¢ TL;DR: #Echidna š¦integrates scRNA-seq & WGS to decouple gene dosage effects on phenotypic plasticity, tracks clonal evolution, and identifies resistance drivers in tumors.
Read more here: www.biorxiv.org/content/10.1...
Letās unravel tumor evolution, one clone at a time! 7/7
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š Why is this impactful? #Echidna doesnāt require joint scDNA/RNA sequencing (rare/expensive). Instead, it pairs scRNA-seq & WGSāreadily obtainable from clinical samples. Itās scalable & can reveal mechanisms of cancer progression & treatment response! š§¬ 6/
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A Case Study in Melanoma: š§¬ Clones resistant to anti-PD-1 therapy showed clusters of phenotype-defining genes in hotspots of amplification! Including:
S100 family and MHC-II genes. #Echidna also disentangles intrinsic (CNA-driven) vs extrinsic expression immune signaling!
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What did we find? Applied to tumor samples: 1ļøā£ Clonal structure reconstructed with higher accuracy vs InferCNV/Numbat. 2ļøā£ Temporal dynamics captured: tracks clonal evolution pre/post therapy. 3ļøā£ Drivers of resistance identified using GDX in genomic hotspots. 4/
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How it works: #Echidna models single-cell RNA & bulk WGS data using a Bayesian hierarchical framework. Key features:
Deconvolves CNA profiles
Tracks clones & their phenotypic states over time
Introduces GDX: a metric quantifying gene dosage effects! 3/
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š Why Echidna? Phenotypic plasticity (cell adaptability) is critical in cancer progression & resistance. But how much of this plasticity is driven by gene dosage vs external cues?
Echidna uncouples these effects, bridging genome & transcriptome across timepoints!