Article

Expression-based species deconvolution and realignment removes misalignment error in multispecies single-cell data

2021-04-05

Abstract excerpt

Although single-cell RNA sequencing of xenograft samples has been widely used, no comprehensive bioinformatics pipeline is available for human and mouse mixed single-cell analyses. Considering the numerous homologous genes across the human and mouse genomes, misalignment errors should be evaluated, and a new algorithm is required. We assessed the extents and effects of misalignment errors when using human and mous...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: a0131633-491b-547d-b6d9-ca7b64747576
DOI: 10.1101/2021.04.04.438147

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Expression-based species deconvolution and realignment removes misalignment error in multispecies single-cell dataDOI 10.1101/2021.04.04.438147Read

Optimized splitting of RNA sequencing data by speciesSemantic proximity Read

Data Matrix Normalization and Merging Strategies Minimize Batch-specific Systemic Variation in scRNA-Seq DataSemantic proximity Read

10x Genomics Gene Expression Flex is a powerful tool for single-cell transcriptomics of xenograft modelsSemantic proximity Read

Strategies for Integrating Single-Cell RNA Sequencing Results With Multiple SpeciesSemantic proximity Read

Massively parallel nanowell-based single-cell gene expression profilingSemantic proximity Read

A Risk-reward Examination of Sample Multiplexing Reagents for Single Cell RNA-SeqSemantic proximity Read

The effect of background noise and its removal on the analysis of single-cell expression data.Semantic proximity Read

Real-paired single-cell/bulk RNA-seq benchmark and a practical protocol for accurate cell-type deconvolution in human BAL samplesSemantic proximity Read

Cross-species imputation and comparison of single-cell transcriptomic profilesSemantic proximity Read

Enabling cross-study analysis of RNA-Sequencing dataSemantic proximity Read

Deconvolution of Sparse-count RNA Sequencing Data for Tumor Cells Using Embedded Negative Binomial DistributionsSemantic proximity Read

Single-cell transcriptomics for the 99.9% of species without reference genomesSemantic proximity Read