Nov 26, 2014 · In this study, an algorithm was developed to detect the bias of multiple displacement amplification and the relation between GC content and ...
To overcome these challenges, cell stabilization and unbiased whole genome amplification are required. This study investigates the performance of four WGA ...
Apr 30, 2018 · Here we propose a robust model, BCseq (bias-corrected sequencing analysis), to accurately quantify gene expression from scRNA-seq. BCseq ...
Missing: GC | Show results with:GC
Our model produces single base pair prediction, allowing optimal correction regardless of the required downstream smoothing. Finally, this provides empirical ...
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Jun 24, 2011 · GC-content bias describes the dependence between fragment count (read coverage) and GC con- tent found in high-throughput sequencing assays, ...
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Sep 15, 2019 · EM algorithm for correction of GC content bias. GC content bias f(GC), EM fitting, and cross-sample segmentation results of scDNA-seq data ...
Jun 19, 2018 · Overall, we hope that the developed pipeline will facilitate analysis of droplet-based single-cell RNA-seq data, providing helpful diagnostics ( ...
Apr 16, 2015 · Although such random bias cannot be corrected systematically, it suggests an efficient census-based strategy to accurately determine somatic ...
This empirical evidence strengthens the hypothesis that PCR is the most important cause of the GC bias. We propose a model that produces predictions at the base ...
A recent approach by Li et al. named DESC [36] allows for the correction of batch effects and clustering of cell types in an iterative fashion, using an ...