Figure 4: Variant detection in single-cell genomes.

(a) Census-based variant calling requires that acceptable variants be observed in at least two independent single-cell libraries. (b) Estimates of the census-based detection sensitivity for a population of independently amplified single-cell libraries all assumed to have similar amplification bias as GBM #4 (Supplementary Fig. 11). Optimal detection sensitivity is achieved at roughly 0.5 × depth-per-library regardless of the sub-clonal fraction or the total sequencing depth. (c) Optimal depth-per-library for census-based variant detection in a population of independently amplified single-cell libraries assumed to have similar coverage bias. The range of the optimal depths is calculated on the basis of the amplification bias observed in single glioblastoma libraries in Fig. 2b. For libraries with more bias or for the detection of variants with lower clonal fractions, it is optimal to sequence more libraries at modest depths (0.1–0.5 × ). (d) Observed coverage of reference and alternate bases at heterozygous SNP sites in disomic Chr. 5 as an estimate of the census-based detection sensitivity for clonal variants. A varying number of single glioblastoma nuclei (59, 22 and 2) were sequenced to the same total depth (20 × ) and genotyped at germline heterozygous SNP sites. Group (A) included two cells with the best uniformity and group (B) included two cells with average uniformity. For either heterozygous coverage or the detection of alternate bases, the larger pools offer better sensitivity than the two groups of two cells. (e) Comparison between somatic non-synonymous variants detected in different-sized pools of single cells sequenced to the same total depths (20 × ). The truth set (48 variants in total) included 43 variants that were detected in both 30 × whole-genome and 120 × whole-exome sequencing of bulk tumour DNA, plus five additional variants detected in bulk whole-genome and single-cell sequencing. At the same overall sequencing depth, census-based detection from a population of cells (59 and 22) offers higher sensitivity and better specificity over deep sequencing of two libraries. A larger number of private/false positive mutations are observed when individual samples are sequenced to higher depths, and these private calls often arise from sporadic sequencing errors that coincide with amplification errors.