Data independent acquisition (DIA) methods have revolutionised the field of LC-MS based proteomics by increasing sample-throughput, enhanced data-completeness and, importantly, reducing the required sample input. However, truly comprehensive global proteomics remains difficult, due to the large dynamic range of protein abundances, differing by >6 orders of magnitude. Several methods have been developed to delve deeper into the proteome, including gas-phase fractionation (GPF) techniques (PAcIFIC, AIF, PulseDIA) (1-3) as well as SWATH-MS (4), which can dramatically increase the number of peptides and proteins that can be profiled through the generation of spectral libraries which has been shown to perform comparably to deep offline fractionation-based libraries for DIA data analysis. One advantage GPF has over older, offline fractionation-based techniques is that it requires less sample input. This is particularly useful for low abundant samples, such as in vivo cell populations. Here, we investigate how GPF-DDA and GPF-DIA techniques can be employed in tandem to profile the phosphoproteomes in these low abundant samples.