Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. This list is enriched for components of the proteasome (ex. PSMA1) and spliceosome (ex. SF3B2), and also includes the translation initiation factor EIF4H, and many heterogeneous nuclear ribonucleoprotein genes (ex. HNRNPL). We have validated the consistency of our new control genes in 1933 cancer and normal tissues using publically available RNA-seq data, and their usefulness in qRT-PCR analysis is clearly demonstrated.