Abstract: Objective To compare the detection results of the copy number variations analysis pipeline based on high-throughput sequencing (PICNIC) and conventional array comparative genomic hybridization. Methods We enrolled patients underwent both aCGH detection and high-throughput sequencing in Children's Hospital of Fudan University from January 1, 2016 to December 31, 2017. Informed consent was obtained from the parents. We have established an operational pipeline (PICNIC) which detect, annotate and prioritize CNVs from raw high-throughput sequencing data combined with clinical information for disease diagnosis. The CNVs identification between aCGH platform and the PICNIC pipeline were compared to prove the utility value of PICNIC. The aCGH platform used the Agilent's SurePrint 180K Kit for experiment and specific softwares for data processing and copy number variation identification. Detected CNVs with duplications >500 kb and deletions >200 kb were remained for further analysis. With the manually evaluation of the patient's clinical phenotypes and the CNV's function, Pathogenic/Likely-pathogenic (P/LP) were concluded for the CNVs that reported phenotypes were in accordance with the patients phenotypes while Variants of Unknown Significance (VUS) for the not exactly matched ones. The PICNIC analysis pipeline started with the BAM file generated from the sequencing data. After the exon coverage depth calculation and the quality control, CANOES was used for the CNVs detection. The detected CNVs were further annotated and filtered for both gene level and regional level. The detection rate and sensitivity of these two methods were compared.In this study, we performed aCGH and PICNIC on 113 samples and compared the result of CNVs detection between these two methods. Results Altogether, 113 cases underwent both aCGH detection and PICNIC analysis were enrolled, with an average age of 2 years old. The patients including 82 developmental delay cases, 16 seizures cases, 5 autism cases, 3 congenital heart disease cases and 7 genetic counseling cases. The aCGH test detected 76 P/LP CNVs and 16 VUS CNVs while PICNIC detected 92 P/LP CNVs and 21 VUS CNVs. All of the P/LP and VUS CNVs detected by aCGH were consistently detected by PICNIC and 16 VUS CNVs detected by aCGH were concluded as P/LP by PICNIC. Taking aCGH as the gold standard, the detection of PICNIC showed that sensitivity was 100% (95% CI: 94%-100%), specificity was 100% (95% CI: 81%-100%), positive predictive value was 82.6% (95% CI: 73%-89%), and negative predictive value was 56.8% (95% CI :40%-72%). Among the 446 aCGH detected CNVs, PICNIC verified 190 of them; among the 236 CNVs detected by PICNIC, aCGH identified 190 of them. Conclusion The CNVs analysis pipeline based on high throughput sequencing (PICNIC) demonstrated 100% specific and sensitive to Pathogenic/Likely pathogenic CNVs, and could be used in clinical detection. The establishment of this method and its clinical popularization were of great significance for further high-throughput capture sequencing data mining and re-analyzing.