The data set for testing cellCounts

The 10x Chromium single-cell RNA sequencing technology is a powerful gene expression profiling platform, which is capable of profiling expression of thousands of genes in tens of thousands of cells simultaneously. This platform can produce hundreds of million reads in a single experiment, making it a very challenging task to quantify expression levels of genes in individual cells due to the massive data volume. Here we present cellCounts, a new tool for efficient and accurate quanti-fication of 10x Chromium. cellCounts employs the seed-and-vote strategy to align reads to a refer-ence genome, collapses reads to UMIs (Unique Molecular Identifier) and then assigns UMIs to genes based on the featureCounts program. Using multiple real datasets, we showed that cell-Counts is ~3 times faster than cellRanger, a popular quantification program developed by 10x. Using simulation and real datasets with built-in ground truth, we demonstrated that cellCounts is markedly more accurate than cellRanger, cellCounts is implemented in R, making it easily inte-grated with other R programs for analysing Chromium data.