Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold-level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on synteny between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here, we present “sex assignment through coverage” (SATC), a method to assign sex to samples and identify sex-linked scaffolds from next generation sequencing (NGS) data. The method works for species with a homogametic/heterogametic sex determination system and only requires a scaffold-level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: (i) male and female individuals, and (ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is freely available at https://github.com/popgenDK/SATC as R code and a graphical user interface (GUI).