Quantitative cellular imaging with coherent Raman microscopy reveals morphological characteristics and chemical composition at the single-cell level.  Meanwhile recent advances in high-throughput sequencing have enabled whole-transcriptome profiling of gene expression in single cells. Both measurements can uncover heterogeneity in cellular populations that would otherwise be obscured in ensemble measurement. Furthermore both imaging and gene expression profiling can be used to quantify cell state during differentiation. However, in order to infer the relationship between gene expression and morphological phenotypes, it is necessary to image and sequence the same single cell. We use a microfluidic platform to couple imaging and RNA sequencing of single cells and present recent developments on how to analyze large, multimodal, single-cell datasets.