Sentence examples for global imputation from inspiring English sources

Algorithms used can be divided into two categories: local imputation algorithms and global imputation algorithms.

For global imputation algorithms, we used singular value decomposition (SVDimpute) and Bayesian principal components analysis (BPCA).

We used the nCounter® platform and global imputation to ask whether in vivo parasite samples cluster by organ or by patient, and to detect genes that are overexpressed by parasites sequestered in human tissues (Table  1).

Notably, SNR rankings derived from the measured data were comparable with the rankings observed following all forms of data imputation and the global imputed dataset exhibited higher overall SNR values.

GL2P consists of two components: a local similarity measurement module and a global weighted imputation module.

Impute: impute: Imputation for microarray data.

Here we show how adaptation of two existing tools - the nCounter® platform and imputation of global gene expression - can be leveraged to uncover the expression profiles of in vivo sequestered malaria parasites.

Full-scale prediction of global expression profiles using established imputation methods allowed us to query the expression of nearly 3,700 genes from just 60 landmarks.

We also use whole-genome imputation to generate global transcriptional profiles for each sample, providing a first look at the gene expression profiles of in vivo sequestered malaria parasites.

We also used imputation to generate global transcriptional profiles and assessed differential gene expression between parasites growing in vitro and those recovered from malaria-infected patient tissues collected at autopsy.

It is noted that our proposed hybrid imputation approach incorporates both global and local information of microarray genes, which achieves lower NRMSE values against to any single approach only.