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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
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
DCEG Imputation Reference Dataset
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 | PXD023040 | Pride
Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is stil...
ORGANISM(S): Homo Sapiens (human) Saccharomyces Cerevisiae (baker's Yeast) Drosophila Melanogaster (fruit Fly) 
Imputation Accuracy of DogsLife Labrador Retrievers Sequenced at Varying Read Depth
This data set includes the following summary level data file used for the imputation data: imputation.sv.assoc.txt: results from single variant association analysis in imputed samples
Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years
Genomics
Rice Imputation Project
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