Regulatory agencies advise to use the most conservative approach to impute missing data. As a drawback, single imputation methods do not take into account imputation variability.Giulia ToniniPhD Menarini RicercheFlorence
The advent of low cost next generation sequencing has made it possible to sequence a large number of dairy and beef bulls which can be used as a reference for imputation of whole genome sequence data. The aim of this study was to investigate the accuracy and speed of imputation from a high...
Multiple studies have highlighted dysregulation of complex networks of peripheral blood immune responses in COVID-19, using single-cell RNA-sequencing (scRNA-seq) analysis5,6,7,8,9,10,11,12,13,14. Monocytes5,6,7,8,9, antigen-presenting cells10, natural killer (NK) cells5,6,11, T cells...
While most of the current epigenomic single-cell technologies are unimodal (Supplementary Table 3), several studies have attempted to profile two epigenetic modalities at the same time through direct measurement28,29 or imputation from other co-profiled modality20,23. Profiling of three epigenetic mod...
While current imputation methods provide improved gene expression information, they still rely on the comparison of similar cells with largely absent gene expression information, for example by using clustering approaches. Genes that are not expressed in neighboring cells cannot be imputed, limiting the ...
Platelet counts were considered as nonresponse if they were missing after imputation. The proportion of patients who underwent splenectomy during the study was summarized. The exposure-adjusted incidence rates and patient incidence rates of AEs were summarized by system organ class and by preferred term...
An important goal of whole-genome studies concerned with single nucleotide polymorphisms (SNPs) is the identification of SNPs associated with a covariate of interest such as the case-control status or the type of cancer. Since these studies often compris
summarized in Additional file4. We performed functional clustering with DAVID [62] using genes with significant DTU (adjustedP-value < 0.01) as input (Additional file5). The transcript structures in all figures were plotted usinggeom_alignmentinggbio[63] (1.36.0). We performed imputation of ...
Post-hoc analyses were performed to quantify the potential of missing data for primary outcomes only: multiple imputation for missing at random was used,23 with M = 20 imputations and adjustment of the imputation model for site, age, number of urinary symptoms and signs, previous antibiotic...
[12]. Data processing primarily involves reading mapping, normalization, batch correction, and missing data imputation, whereas data analysis involves dimensionality reduction, differential expression analysis, and cell clustering [13]. Studies assessing the performance of different single-cell RNA sequencing...