SCRABBLE: single-cell RNA-seq imputation constrained by bulk RNA-seq data
نویسندگان
چکیده
منابع مشابه
Locality Sensitive Imputation for Single-Cell RNA-Seq Data
One of the most notable challenges in single cell RNA-Seq data analysis is the so called drop-out effect, where only a fraction of the transcriptome of each cell is captured. The random nature of drop-outs, however, makes it possible to consider imputation methods as means of correcting for drop-outs. In this paper we study some existing scRNA-Seq imputation methods and propose a novel iterativ...
متن کاملnetSmooth: Network-smoothing based imputation for single cell RNA-seq
Single cell RNA-seq (scRNA-seq) experiments suffer from a range of characteristic technical biases, such as dropouts (zero or near zero counts) and high variance. Current analysis methods rely on imputing missing values by various means of local averaging or regression, often amplifying biases inherent in the data. We present netSmooth, a network-diffusion based method that uses priors for the ...
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Background - MaterialsAndMethods N;Results N;Conclusion N;
متن کاملDetecting heterogeneity in single-cell RNA-Seq
21 Single-cell RNA-Sequencing (scRNA-Seq) is a cutting edge technology that enables the 22 understanding of biological processes at an unprecedentedly high resolution. However, 23 well suited bioinformatics tools to analyze the data generated from this new technology 24 are still lacking. Here we have investigated the performance of non-negative matrix 25 factorization (NMF) method to analyze a...
متن کاملscImpute: accurate and robust imputation for single cell RNA-seq data
The analysis of single-cell RNA-seq (scRNA-seq) data is complicated and biased by excess zero or near zero counts, the so-called dropouts due to the low amounts of mRNA sequenced within individual cells. We introduce scImpute, a statistical method to accurately and robustly impute the dropouts in scRNA-seq data. scImpute is shown as an effective tool to enhance the clustering of cell population...
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ژورنال
عنوان ژورنال: Genome Biology
سال: 2019
ISSN: 1474-760X
DOI: 10.1186/s13059-019-1681-8