Processed data for: Empirical Estimation of Ambient Contamination in Combinatorial Single-Cell Methods Using Multi-Reference Mapping

Processed inputs read by every figure and supplementary-table script of the paper (Gomez-Cano, Jiang, Welch and Marand, bioRxiv 2026, https://doi.org/10.64898/2026.09.11.750809), so that all figures and tables can be rebuilt from public files: this record, the GEO deposit of the maize and Arabidopsis scifi-ATAC-seq library (series GSE348516, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE348516), and the companion code repository (https://github.com/gomezcan/ambientmapper_manuscript). Software: AmbientMapper (https://github.com/gomezcan/ambientmapper) and scifi-demux (https://github.com/gomezcan/scifi-demux). One tar.gz per data group (27 archives). Each unpacks to <group>/<path>; README.md documents every group, the dataset and stage names, and the files that live on GEO instead. manifest.tsv lists every file with its size and the panels it serves; MD5SUMS covers the archives and MD5SUMS.files every file inside them. Dataset names: AtZm_scifiATAC_combinedRef (the maize and Arabidopsis library mapped to the concatenated reference), AtZm_scifiATAC_indepRef (the same library mapped to each genome independently), ZmRoot_scATAC (Marand et al. 2021, SRR12331466), B73Mo17_scifiATAC_rep1 and _rep2 and multiGenotype_scifiATAC (Zhang et al. 2024, PRJNA996051), and the read-level synthetic benchmark.