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scPred: Cell type prediction at single-cell resolution

https://doi.org/10.1101/369538
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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An Introduction to Statistical Learning
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Double immunohistochemistry enhances detection of lymphatic and venous invasion in early-stage colorectal cancer
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A combination of immunohistochemistry and molecular approaches improves highly sensitive detection of BRAF mutations in papillary thyroid cancer
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Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells
inferredcites →https://doi.org/10.1016/j.cell.2015.05.002openalex-snapshot
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets
inferredcites →https://doi.org/10.1016/j.cell.2015.10.039openalex-snapshot
Design and Analysis of Single-Cell Sequencing Experiments
inferredcites →https://doi.org/10.1016/j.cell.2016.08.009openalex-snapshot
Single-Cell RNA-Seq Reveals Lineage and X Chromosome Dynamics in Human Preimplantation Embryos
inferredcites →https://doi.org/10.1016/j.cell.2016.11.039openalex-snapshot
Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq
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A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure
inferredcites →https://doi.org/10.1016/j.cels.2016.09.002openalex-snapshot
A Single-Cell Transcriptome Atlas of the Human Pancreas
inferredcites →https://doi.org/10.1016/j.cels.2016.10.009openalex-snapshot
Surprising Heterogeneity of Pancreatic Islet Cell Subsets
inferredcites →https://doi.org/10.1016/j.cmet.2016.08.018openalex-snapshot
RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes
inferredcites →https://doi.org/10.1016/j.cmet.2016.08.020openalex-snapshot
Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes
inferredcites →https://doi.org/10.1016/j.stem.2017.05.009openalex-snapshot
Single-Cell RNA-Seq Analysis Maps Development of Human Germline Cells and Gonadal Niche Interactions
inferredcites →https://doi.org/10.1038/nature13173openalex-snapshot
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
inferredcites →https://doi.org/10.1038/nature14966openalex-snapshot
Single-cell messenger RNA sequencing reveals rare intestinal cell types
inferredcites →https://doi.org/10.1038/nature18323openalex-snapshot
Dissecting direct reprogramming from fibroblast to neuron using single-cell RNA-seq
inferredcites →https://doi.org/10.1038/nbt.2325openalex-snapshot
Transcriptome sequencing of single cells with Smart-Seq
inferredcites →https://doi.org/10.1038/nbt.2702openalex-snapshot
Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories
inferredcites →https://doi.org/10.1038/nbt.3854openalex-snapshot
Single-cell topological RNA-seq analysis reveals insights into cellular differentiation and development
inferredcites →https://doi.org/10.1038/nbt.4096openalex-snapshot
Integrating single-cell transcriptomic data across different conditions, technologies, and species
inferredcites →https://doi.org/10.1038/ng.3818openalex-snapshot
Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors
inferredcites →https://doi.org/10.1038/nmeth.2639openalex-snapshot
Smart-seq2 for sensitive full-length transcriptome profiling in single cells
inferredcites →https://doi.org/10.1038/nmeth.4236openalex-snapshot
SC3: consensus clustering of single-cell RNA-seq data
inferredcites →https://doi.org/10.1038/nrg.2016.127openalex-snapshot
The origin and evolution of cell types
inferredcites →https://doi.org/10.1038/nrg3833openalex-snapshot
Computational and analytical challenges in single-cell transcriptomics
inferredcites →https://doi.org/10.1038/nri.2017.76openalex-snapshot
Single-cell RNA sequencing to explore immune cell heterogeneity
inferredcites →https://doi.org/10.1038/srep14634openalex-snapshot
A 3D map of the islet routes throughout the healthy human pancreas
inferredcites →https://doi.org/10.1073/pnas.1508057112openalex-snapshot
Systematic transcriptome analysis reveals tumor-specific isoforms for ovarian cancer diagnosis and therapy
inferredcites →https://doi.org/10.1084/jem.20161135openalex-snapshot
Human dendritic cells (DCs) are derived from distinct circulating precursors that are precommitted to become CD1c+ or CD141+ DCs
inferredcites →https://doi.org/10.1093/bioinformatics/btp616openalex-snapshot
edgeR : a Bioconductor package for differential expression analysis of digital gene expression data
inferredcites →https://doi.org/10.1126/science.aah4573openalex-snapshot
Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors
inferredcites →https://doi.org/10.1126/scitranslmed.aan4730openalex-snapshot
Single-cell analyses to tailor treatments
inferredcites →https://doi.org/10.1137/04060593xopenalex-snapshot
Augmented Implicitly Restarted Lanczos Bidiagonalization Methods
inferredcites →https://doi.org/10.1158/0008-5472.can-03-2879openalex-snapshot
Mismatch Repair Gene PMS2
inferredcites →https://doi.org/10.1158/1078-0432.ccr-16-3187openalex-snapshot
The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection
inferredcites →https://doi.org/10.1186/s13059-016-0938-8openalex-snapshot
CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq
inferredcites →https://doi.org/10.1201/b10328openalex-snapshot
Data Mining with R
inferredcites →https://doi.org/10.1371/journal.pcbi.1000173openalex-snapshot
Support Vector Machines and Kernels for Computational Biology
inferredcites →https://doi.org/10.18637/jss.v011.i09openalex-snapshot
kernlab - An S4 Package for Kernel Methods in R
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Building Predictive Models in R Using the caret Package
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Current and future biomarkers in colorectal cancer
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Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.isci.2021.102855openalex-snapshot
A reference-free approach for cell type classification with scRNA-seq
inferred← citeshttps://doi.org/10.1038/s41576-019-0093-7openalex-snapshot
Integrative single-cell analysis
inferred← citeshttps://doi.org/10.1101/2020.09.22.307512openalex-snapshot
MarkerCapsule: Explainable Single Cell Typing using Capsule Networks
inferred← citeshttps://doi.org/10.1101/456129openalex-snapshot
Moana: A robust and scalable cell type classification framework for single-cell RNA-Seq data
inferred← citeshttps://doi.org/10.1158/1078-0432.ccr-19-3231openalex-snapshot
Single-Cell Genomic Characterization Reveals the Cellular Reprogramming of the Gastric Tumor Microenvironment
inferred← citeshttps://doi.org/10.1186/s13059-019-1795-zopenalex-snapshot
A comparison of automatic cell identification methods for single-cell RNA sequencing data
inferred← citeshttps://doi.org/10.12688/f1000research.18490.1openalex-snapshot
Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data
inferred← citeshttps://doi.org/10.12688/f1000research.18490.2openalex-snapshot
Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data
inferred← citeshttps://doi.org/10.12688/f1000research.18490.3openalex-snapshot
Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing data
inferred← citeshttps://doi.org/10.15252/msb.20199389openalex-snapshot
scClassify: sample size estimation and multiscale classification of cells using single and multiple reference
inferred← citeshttps://doi.org/10.3389/fgene.2022.788832openalex-snapshot
A Regularized Multi-Task Learning Approach for Cell Type Detection in Single-Cell RNA Sequencing Data
inferred← citeshttps://doi.org/10.7554/elife.52155openalex-snapshot
The single-cell eQTLGen consortium
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