In my thesis, I present four studies to explore astrophysical methods for understanding dark matter properties. To understand the nature of dark matter, I explore a few unstable dark matter models that are invoked as ways to address apparent discrepancies between the predictions of standard cold dark matter and observations of small-scale galactic structure. My studies are aimed at developing independent large-scale constraints on these models. One of the model is a decaying dark matter model such that one dark matter particle decays into two relativistic non-interacting particles. In the second model, a dark matter particle decays into a less massive, stable dark matter particle with a recoil kick velocity Vk and a relativistic non-interacting particle. I consider two types of experiments: one is weak lensing cosmic shear with future or forthcoming surveys like Dark Energy Survey (DES) and Large Synoptic Survey Telescope (LSST); the other one is Lyman-alpha forest spectrum, which has contemporary data from Sloan Digital Sky Survey (SDSS) and other observations. I found that large-scale structure growth is sensitive to the change of dark matter properties due to these decay processes, and they can provide competitive constraints comparing to other existing limits. On small scale, the gravitational interplay of baryon and dark matter can affect the clustering of dark matter. I examine adiabatic contraction (AC) models what are traditionally used to parametrize the dark matter response to the cooling of baryons by investigating a suite of numerical simulations. We found that the errors in AC reconstructions are correlated with baryonic physics and certain halo properties. Our results indicate that existing AC models need significant calibration in order to predicting realistic matter distribution