Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
暂无分享,去创建一个
Laleh Haghverdi | John C Marioni | Aaron T L Lun | Michael D Morgan | J. Marioni | Laleh Haghverdi | A. Lun | M. Morgan | L. Haghverdi | Michael D. Morgan
[1] Matthieu Latapy,et al. Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..
[2] Cheng Li,et al. Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.
[3] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[4] Aleksandra A. Kolodziejczyk,et al. Accounting for technical noise in single-cell RNA-seq experiments , 2013, Nature Methods.
[5] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[6] Åsa K. Björklund,et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells , 2013 .
[7] Sean C. Bendall,et al. Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development , 2014, Cell.
[8] I. Amit,et al. Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types , 2014, Science.
[9] S. Dudoit,et al. Normalization of RNA-seq data using factor analysis of control genes or samples , 2014, Nature Biotechnology.
[10] Jeffrey T. Leek. svaseq: removing batch effects and other unwanted noise from sequencing data , 2014 .
[11] Wei Shi,et al. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features , 2013, Bioinform..
[12] Fabian J. Theis,et al. destiny: diffusion maps for large-scale single-cell data in R , 2015, Bioinform..
[13] Matthew E. Ritchie,et al. limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.
[14] Allon M. Klein,et al. Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.
[15] Evan Z. Macosko,et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.
[16] Chen Xu,et al. Identification of cell types from single-cell transcriptomes using a novel clustering method , 2015, Bioinform..
[17] I. Amit,et al. Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors , 2015, Cell.
[18] Sean C. Bendall,et al. An interactive reference framework for modeling a dynamic immune system , 2015, Science.
[19] Grace X. Y. Zheng,et al. Massively parallel digital transcriptional profiling of single cells , 2016, bioRxiv.
[20] J. Marioni,et al. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts , 2016, Genome Biology.
[21] Samuel L. Wolock,et al. A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure. , 2016, Cell systems.
[22] Mauro J. Muraro,et al. De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data , 2016, Cell stem cell.
[23] Nicola K. Wilson,et al. Resolving Early Mesoderm Diversification through Single Cell Expression Profiling , 2016, Nature.
[24] Nicola K. Wilson,et al. A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation. , 2016, Blood.
[25] Mauro J. Muraro,et al. A Single-Cell Transcriptome Atlas of the Human Pancreas , 2016, Cell systems.
[26] David A. Knowles,et al. Batch effects and the effective design of single-cell gene expression studies , 2016, bioRxiv.
[27] D. M. Smith,et al. Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes , 2016, Cell metabolism.
[28] Fabian J. Theis,et al. Assessment of batch-correction methods for scRNA-seq data with a new test metric , 2017, bioRxiv.
[29] J. C. Love,et al. Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput , 2017, Nature Methods.
[30] J. George,et al. Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes , 2017, Genome research.
[31] R. Irizarry,et al. Missing data and technical variability in single‐cell RNA‐sequencing experiments , 2018, Biostatistics.