Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue.

"once the puncta counting was completed the object data and settings were exported as csv files (available via globus at "jhpce#treg_paper") and txt files (available on github) respectively.; availability of data and materials the snrna-seq data [ 20 ] is available from https://github com/lieberinstitute/10xpilot_snrnaseq-human#processed-data [ 53 ]."

"once the puncta counting was completed the object data and settings were exported as csv files (available via globus at "jhpce#treg_paper") and txt files (available on github) respectively.; availability of data and materials the snrna-seq data [ 20 ] is available from https://github com/lieberinstitute/10xpilot_snrnaseq-human#processed-data [ 53 ].; the code for the analysis is available from https://github com/lieberinstitute/treg_paper [ 54 ] and the software from https://github com/lieberinstitute/treg [ 22 ]."

"Declarations Ethics approval and consent to participateNot applicable. Consent for publicationNot applicable. Competing interestsThe authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests."

"Funding This project was supported by the Lieber Institute for Brain Development, National Institutes of Health grant R01 MH123183 (LAHM, KDM, SHK, SCP, SCH, KRM, LCT) and CZF2019-002443 (SCH) from the Chan Zuckerberg Initiative DAF, and an advised fund of Silicon Valley Community Foundation. All funding bodies had no role in the design of the study; collection, analysis, and interpretation of the data; and writing the manuscript."