Background: Targeted sequencing of circulating tumor DNA (ctDNA) has been used in early tumor detection and guidance of clinical cancer treatment. Accurate somatic copy number variation (SCNV) estimation is useful for better decisions in clinics, but remain challenging due to low percentage of tumor-cell-released DNA in circulating blood, in addition to the low signal-noise ratio and usual lack of normal control. 

Methods: To overcome these challenges and call SCNV at gene level, we develop a novel bioinformatics tool ctCNV. After correction for GC content, target region length and read counts, genome local scores at the gene level (GCS) were calculated, using 30 normal blood samples as control. Statistically significant cutoffs were determined using control. 

Results: The new method has been benchmarked with other SCNV calling tools such as CNVkit, which have been developed mainly for whole exome sequencing instead of targeted DNAseq. The validation experiment involves 6 mixed samples consisting of different proportions of known cell lines and real blood samples. ROC curve obtained through comparing the SCNV calling results with Droplet Digital PCR results show improvement of our method comparing to existing methods. 

Conclusions: As a summary, our study has three main results/contributions. First, we developed a novel computational tool for SCNV calling in targeted sequencing of ctDNA, with good sensitivity and specificity. Second, we thoroughly evaluated the performance of current available CNV calling tools in targeted sequenced ctDNA. Third, the raw data generated from our six real samples of gradient mixture of different cell lines and human’s samples can serve as an evaluation standard to other further computational tools for CNV calling in targeted sequenced ctDNA.