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ProteomicsComBat HarmonizR enables the integrated analysis of independently generated proteomic datasets through data harmonization with appropriate handling of missing values
The integration of proteomic datasets, generated by non-cooperating laboratories using different LC-MS/MS setups can overcome limitations in statistically underpowered sample cohorts but has not been demonstrated to this day. In proteomics, differences in sample preservation and preparation strateg...
ORGANISM(S): Mus musculus (Mouse) Homo sapiens (Human) Escherichia coli Saccharomyces cerevisiae (Baker's yeast) 
2022-05-23 | PXD027467 | Pride
Swath Metastudy Missing values Dda Dia Tmt Data integration Ffpe Silac Tissue Harmonisazion Fresh-frozen Combat 
UnknownOptimal clustering with missing values.
Not available
S-EPMC6584727 | biostudies-literature
UnknownHandling missing values in the MDS-UPDRS.
Not available
S-EPMC5072275 | biostudies-literature
UnknownBenchmarking missing-values approaches for predictive models on health databases.
Not available
S-EPMC9012100 | biostudies-literature
UnknownNew insights into handling missing values in environmental epidemiological studies.
Not available
S-EPMC4165576 | biostudies-literature
UnknownRecurrent Neural Networks for Multivariate Time Series with Missing Values.
Not available
S-EPMC5904216 | biostudies-literature
UnknownAdvanced methods for missing values imputation based on similarity learning.
Not available
S-EPMC8323724 | biostudies-literature
ProteomicsDilution Series imputation, LC MS/MS
Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating i...
ORGANISM(S): Homo sapiens (Human) 
2021-05-07 | PXD023012 | Pride
Dia-ms Ovarian cancer Imputation Dilution series 
ProteomicsPilot data for Imputation, LC-MS/MS
Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating i...
ORGANISM(S): Homo sapiens (Human) 
2021-05-07 | PXD022996 | Pride
Dia-ms Ovarian cancer Imputation 
UnknownDo Missing Values Influence Outcomes in a Cross-sectional Mail Survey?
Not available
S-EPMC7930870 | biostudies-literature
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