pysigscore: gene signatures scoring across bulk and single-cell transcriptomics
High-throughput transcriptomics has made gene signatures central to interpreting gene expression data, with applications in diagnosis, prognosis, and prediction. Quantifying signature activity and assessing its robustness remain challenging because scoring methods primarily rely on various assumptions, and no single approach is universally optimal. Here, we present pysigscore, a Python framework…
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