GEOapplication/xmlftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE328nnn/GSE328457/primary200OKTranscriptomicsHomo sapiensExpression profiling by high throughput sequencinghttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE328457GEOGSEfalsePooled combinatorial screening identifies transcription factor sets that drive hematopoietic progenitor-like cell fateMammalian cells can be directed towards specific fates by overexpression of transcription factors (TFs). However, discovering and optimizing which TFs in combination produce a state of interest remains challenging. Here, we develop a scalable screening platform that addresses this challenge by combining high-MOI pooled delivery of barcoded TF ORFs, data augmentation, targeted cell enrichments, and single-cell transcriptomic readouts. As proof of principle, we apply the platform to optimize the generation of hematopoietic stem and progenitor-like cells (HSPCs) from human embryonic stem cells. Our data demonstrate technical performance across a range of key metrics and reveal a richly structured reprogramming fitness landscape over millions of TF combinations. In silico optimization of HSPC-similarity metrics over this landscape revealed two TF combinations that demonstrate superior potency in generating naïve multipotent hematopoietic progenitors relative to gold-standard controls. This study demonstrates a powerful approach for data-driven cell fate engineering using complex combinatorial perturbations.2026/07/12GSE328457GSM9683920GSM9683921GSM9683919GSM9683917GSM9683918GSM9683915GSM9683916GSM9683913GSM9683914GSM9683911GSM9683912GSM9683898GSM9683910GSM9683899GSM9683896GSM9683897GSM9683894GSM9683895GSM9683892GSM9683893GSM9683890GSM9683891GSM9683908GSM9683909GSM9683906GSM9683907GSM9683926GSM9683904GSM9683905GSM9683927GSM9683902GSM9683924GSM9683925GSM9683903GSM9683900GSM9683889GSM9683922GSM9683923GSM968390118573328457Homo sapiens