Nature CommunicationsGenomicsPeer-reviewed journal article
anonymizeBAM: Versatile anonymization of human sequence data for open data sharing
Abstract
The risks associated with re-identification of human genetic data are severely limiting open data sharing in life sciences. Here, we developed anonymizeBAM, a versatile tool for the anonymization of genetic variant information present in sequence data. Applying anonymizeBAM to single-cell RNA-seq and ATAC-seq datasets confirmed the complete removal of donor-related genetic information. Therefore, the accurate generation of de-identified sequence data will re-enable open sharing in sequencing-based studies for improved transparency, reproducibility, and innovation.
- organism: human
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- assay: ATAC-seq
- assay: scRNA-seq
- research focus: variant calling
- research focus: deconvolution
- research focus: database / resource
- research focus: software / tool
- approach: experimental assay
- Citations
- 26
- FWCI
- 1.14
- Field percentile
- top 20%
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