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CDSC:Complete Deconvolution from Bulk Gene Expression by Leveraging Single-cell RNA-Seq Data

Authors: ChenQi Wang;

CDSC:Complete Deconvolution from Bulk Gene Expression by Leveraging Single-cell RNA-Seq Data

Abstract

This dataset contains five different stages: Intra-data, Inter-data_ matched, Inter-data_ unmatched, mixed data and whole blood. Among them, the first three parts are simulation data, and the last two parts are real data. Intra-data contains 5 different simulation bulk data; Inter-data_ matched, Inter-data_ unmatched contains a combination of three types of human pancreatic data and two mouse recurrent cell datasets, totaling 8 sets. The mixture data contains 5 sets of proportional mixed data WholeBlood is a set of real bulk data with three different reference information

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average