Abstract: Germline Copy Number Variation (gCNV) is a type of genomic structural alteration including deletion or duplication of small genomic regions (50bp to 1MB) and can have an important role into cancer etiology. Whole genome sequencing (WGS) has been considered to be the most effective technology for genome-wide identification of gCNVs. However, an easy-to-use gCNV calling pipeline based on WGS data is still lacking. Here, we present the gCNV-Seeker, a user-friendly, rigorous computational pipeline to detect gCNV events based on WGS with standardized quality control and data visualization features. gCNV-Seeker initially adopts GATK probabilistic algorithms to detect a set of raw gCNV events and subsequently applies Binary Segmentation and Pruned Exact Linear Time (PELT) algorithms for re-segmentation and boundary revision of the gCNV candidates, respectively. In addition, gCNV-Seeker is built with several functionalities, including quality control, filtration, annotation and visualization to identify the gCNV regions (gCNVRs) of interest. We applied gCNV-Seeker to the WGS data from 872 lung cancers in never smokers from the Sherlock-Lung study and 3202 WGS data from the 1000 Genomes Project (1KGP) (reference) and identified CNVRs associated with lung cancer risk in never smokers. For example, in comparison to WGS data from 1KGP, we identified several CNVR candidates overlapping with known LC susceptible genes, e.g., the GSTM1/2 homozygous deletion (OR = 1.64, 95% CI=1.43-1.88, P {