Bulk RNA-Seq Deconvolution with single-cell RNA-Seq Datasets

Bulk data of human pancreas

The dataset from Fadista et al. (2014) contains raw read counts data from bulk RNA-seq of human pancreatic islets to study glucose metabolism in healthy and hyper-hypoglycemic conditions. For the purpose of this vignette, the dataset is pre-processed and made available on the data download page. In addition to read counts, this dataset also contains HbA1c levels, BMI, gender and age information for each subject.
 

Single Cell Data of Human Pancreas

The single cell data are from Segerstolpe et al. (2016), which constrains read counts for 25453 genes across 2209 cells. Here we only include the 1097 cells from 6 healthy subjects. The read counts are available on the data download page, in the form of an ExpressionSet.

Another single cell data is from Xin et al. (2016), which have 39849 genes and 1492 cells. The read counts are available on the data download page, in the form of an ExpressionSet.

The deconvolution of 89 subjects from Fadista et al. (2014) are preformed with bulk data GSE50244.bulk.eset and single cell reference EMTAB.eset. We constrained our estimation on 6 major cell types: alpha, beta, delta, gamma, acinar and ductal, which make up over 90% of the whole islet.