19 research outputs found

    MOESM5 of MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers

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    Additional file 5: Results. Monte Carlo simulations results confirmed that substituting the limit of detection (LOD) with LOD/2 does not affect the reliability of ICC estimation; The measurement error structure of peptidomi MALDI-TOF/MS-based analysis of the urinary and serum feature

    MOESM3 of MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers

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    Additional file 3: Table S1. Monte Carlo simulation results. The ICC estimates were obtained by increasing the measurement error (σε) from 0.01 to 0.64 and considering three different limit of detection (LOD) conditions (12.5%, 25% and 50% of values set below LOD) using four different adjustment methods (Richardson and Ciampi’s method, Schisterman’s method, substitution of W < LOD by zeros and substitution of W < LOD by LOD/2). The mean ICCs and Monte Carlo standard errors are shown

    MOESM14 of MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers

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    Additional file 14: MS-Tag search results.  MS-MS spectra, peptide lists and MS-Tag search results (including all the configuration parameter) for the fragmentation patters of the 12 MALDI-TOF/MS serum features
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