Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers

Table 1 Single-cell RNA-seq datasets used

First author	Year	Species	Tissue	Protocol	Cells	Use
Cao [17]	2017	C. elegans	Several	sci-RNA-seq	32,061	Train
Clark [18]	2019	M. musculus	Retina	10x chromium V2	7680	Train
Grun [19]	2016	H. sapiens	Pancreas	CEL-Seq	1726	Train
Klein [20]	2015	M. musculus	Embryonic stem cells	inDrops	2717	Train
Schiebinger [21]	2019	M. musculus	Induced stem cells	10x chromium V2	14,925	Train
Zeisel [22]	2015	M. musculus	Brain	STRT	3005	Train
Zhang [23]	2019	H. sapiens	Synovial/monocytes	CEL-Seq 2	10,001	Train
Macosko [24]	2015	M. musculus	Retina	dropseq	7581	Test
Tung [25]	2016	H. sapiens	Induced stem cells	SMARTer	564	Test
Zheng [26]	2017	H. sapiens	Monocytes	10x gemcode	2612	Test
Vieira Braga [27]	2019	H. sapiens	Lung	dropseq	261	DE
Patel [28]	2014	H. sapiens	Glioblastoma	Smart-seq2	430	Predict
Segerstolpe [29]	2016	H. sapiens	Pancreas	Smart-seq2	1554	Predict

Training data contained only UMI counts. Test and differential expression (DE) data contained UMI counts and read counts. Prediction data contained only read counts

ISSN: 1474-760X