# Introduction X!TandemPipeline (Langella et al. 2017) is a proteomics free and open source Java software program designed to filter and group peptide/protein identifications from MS/MS mass spectra that is used with the MassChroQ quantitative proteomics software (Valot et al. 2011). After a complete rewrite in C++17, the new software, named i2MassChroQ, features native support for the timsTOF raw data format, peptide/protein quantification by merging the features initially in X!TandemPipeline and MassChroQ, and ultimately statistical analysis using either the MSstats or MCQR GNU R package. # Methods i2MassChroQ is written in portable C++17 and makes use of the Qt libraries for the graphical user interface. Binary packages are available for Linux and MS Windows. The timsTOF native raw data reader was developed in-house with the technical specifications provided by Bruker. The sofware was tightly optimized to ensure very fast access to the binary data. The current version provides real time MS/MS peptide annotation and performs extremely fast ion current extractions and XIC chromatogram visualizations. # Results The Bruker timsTOF line of instruments improves the identification of peptides and proteins in complex mixtures by implementing a peculiar ion mobility technology. i2MassChroQ has the distinct feature, with respect to the MaxQuant and MSFragger competitors, of natively parsing the timsTOF raw data with original software code that puts us in total control of the data processing, leveraging speed and accuracy. Our software identifies roughly the same amount of peptides as when using the X!Tandem engine on data provided by the Bruker Data analysis software but performs much faster, reducing processing time from 55 to 12 minutes on a typical HeLa sample quality control LC-MS/MS run. For peptide quantifications, i2MassChroQ uses the ion mobility-enabled version of MassChroQ. Peptide quantification is 20% faster than IonQuant on the same computer. Using benchmark datasets (PXDO1OO12 and PXD014777), we demonstrate that i2MassChroQ identifies and quantifies significantly more proteins, in particular with a better capability to quantify peptides and proteins of lesser abundance, while maintaining extremely low missing data percentages at the feature level (3% in each condition), compared to 56% in some conditions for MS-Fragger. This leads to better protein quantification values by drastically reducing the requirement of missing value imputations.