Replication Data for Proteomic screening identifies PF4/Cxcl4 as a critical driver of myelofibrosis

This dataverse include the LC-MS/MS proteomics datasets of changed proteins generated in the study: "Proteomic screening identifies megakaryocyte-derived PF4/Cxcl4 as a critical driver of myelofibrosis" by Daniele Capitanio, Francesca R. Calledda, Vittorio Abbonante, Daniele Cattaneo, Manuela Moriggi, Niccolò Bartalucci, Cristina Bucelli, Delfina Tosi, Umberto Gianelli, Alessandro Maria Vannucchi, Alessandra Iurlo, Cecilia Gelfi, Alessandra Balduini, and Alessandro Malara. Data were generated by LC-ESI-MS/MS with label-free quantitation. Mass spectra were analyzed using MaxQuant software (Max-Planck-Institute of Biochemistry, Munich, Germany, version 1.6.17.0). Statistical analyses were performed using the Perseus software (Max Planck Institute of Biochemistry, Munich, Germany, version 1.6.15.0). For statistical analysis, Student's t-test with a p-value threshold of 0.05 was applied. To exclude the presence of false positives from the analysis, Benjamini–Hochberg false discovery rate test was applied.