We made a comprehensive investigation of data dependent acquisition workflow for deep c of proteome based on shotgun liquid chromatography-tandem mass spectrometry(LC-MS/MS)from 2016 to 2017.In 2018,we performed a standard sample acquisition study to try to identify LC-MS/MS parameters leading to more identification results.We distributed the same HeLa samples to about 20 Chinese laboratories,which submitted their data sets acquired from different liquid chromatography mass spectrometry(LC-MS)platforms.We evaluated the correlation between the MS2 scanning capacity utilization and scan speed,and interpreted how the MS parameters impacted the performance of DDA to provide a suite of reasonable DDA settings.Following the given optimizing suggestions,several laboratories access almost 100%more proteins by using the same LC-MS platforms.Our centralized analysis show that improving chromatography and maximizing utilization of the MS/MS capacities could significantly improve sampling depth and identifications in proteomics.