ABSTRACT Tear is heterogeneous solution secreted by the lacrimal gland for the lubrication and nutrition of the cornea and protection of conjunctiva from pathogens. Tear is composed of water, ions, electrolytes, lipids, proteins, mucins, and other small molecules. The examination of tear proteins is of prime importance for biomarker studies, prediction and diagnosis of various illnesses. Tear proteins have been examined by various biochemical and analytical techniques. However, the mass spectrometry is considered to be a good choice to analyze low volume tear samples. Our aim was to develop and optimize LC-MS/MS-based proteomics methods for the examination of tear samples. We used the discovery-based proteomic approaches: data dependent acquisition (DDA) and data independent acquisition (DIA) to examine the basal tears collected by capillaries from healthy volunteers. We created a pool of collected samples and performed trypsin digestion. The samples were analyzed using tandem mass spectrometry (LC-MS/MS) using DDA and DIA methods, respectively. The mass spectra for both DDA and DIA were evaluated and analyzed. We wanted to determine the most suitable and reliable method for protein identification in tear samples with the low volumes. At this point of our examinations the DDA method still performs better but with further optimization we would like to enhance the proteome coverage of DIA method. The main outcome of the DIA would be to have a better protein coverage without extended fractionation steps in less analysis time compared to DDA method.