The optimized data analysis pipeline, which was assembled from publicly available tools, slightly exceeded the performance of the Roche gsMapper software with 95% sensitivity and 93% specificity for SNV detection, and subsequent analysis of the Roche/454 data from the T-ALL cell lines and patient samples confirmed previously known oncogenes and tumor suppressors in T-ALL and identified previously unrecognized rare somatic mutations in TET1 and SPRY4 in T-ALL patients. The gene discussed is TET1; the disease is acute lymphoblastic leukemia.