Updated project metadata. Researchers may be interested in finding proteomics runs, which have been deposited into online repositories, that are similar to their own data. However, it is difficult to measure the similarity of a pair of proteomics runs. Here, we present a new method, MS1Connect, that only uses intact peptide scans to calculate the similarity between a pair of runs. We show evidence that the MS1Connect score accurately measures the similarity between two proteomics runs. Specifically, we show that MS1Connect outperforms baseline methods for predicting the species a sample originated. In addition, we show that MS1Connect scores are highly correlated with similarities based o peptide fragment scans by observing a high correlation between MS1Connect scores and the Jaccard index between the sets of confidently detected peptides for a pair of runs.