Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors.

By F. Paul, Ya'ara Arkin, A. Giladi, Diego Jaitin, E. Kenigsberg, Hadas Keren-Shaul, D. Winter, D. Lara-Astiaso, M. Gury, A. Weiner and 12 more. Cell, 2015

849 citations recorded by the source corpus.

Subfields: Hematology, Immunology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/cf98bc3028a9ddbc6003d72850b1b41f09dbf5a2

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Citations in the corpus

Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity (2018, background): “…TFs promoting myelopoiesis (Cebpe, Id1, and Id2) were upregulated in LT-HSCs from b-glucan-treated mice, while lymphopoiesis-related TFs (Pax5, Ebf1, Irf4, Spib, and Lef1) were downregulated (Nimmo et al., 2015; Novershtern et al., 2011; Paul et al., 2015; Rosenbauer and Tenen, 2007) (Figure 5D).”
A Unique Microglia Type Associated with Restricting Development of Alzheimer's Disease. (2017, neutral): “…resolve immune heterogeneity in AD (Deng et al., 2014; Grün et al., 2015; Gury-BenAri et al., 2016; Jaitin et al., 2014; Junker and van Oudenaarden, 2014; La Manno et al., 2016; Mass et al., 2016; Matcovitch-Natan et al., 2016; Paul et al., 2015; Treutlein et al., 2014; Zeisel et al., 2015).”
Wishbone identifies bifurcating developmental trajectories from single-cell data (2016, methodology): “Data processing—The count matrix was downloaded from GEO (GSE72857) [6].”
bigSCale: an analytical framework for big-scale single-cell data (2017, background): “…perfectly correlating genes are discarded as they belong to families with shared 3 ′ -exons (such as Pcdh or Uty ), for which most scRNA-seq techniques (e.g., MARS-Seq [Jaitin et al. 2014; Paul et al. 2015] or chromium-based [Zheng et al. 2017] methods) cannot differentiate between transcripts.”
A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation. (2016, background): “This is supported by the observation that previously defined HSPC populations form coherent groupings on the diffusion map with one major exception—CMPs, which have recently been described as highly heterogeneous.(41,53) Furthermore, although the arrangement of cells in the diffusion map is consiste”
Dissecting Immune Circuits by Linking CRISPR-Pooled Screens with Single-Cell RNA-Seq. (2016, positive): “The plasticity in differentiation and rewiring of response pathways of myeloid cells would have made these results difﬁ-cult to interpret without single-cell analysis coupled to perturbations (Paul et al., 2015).”
Reversed graph embedding resolves complex single-cell developmental trajectories (2017, methodology): “…datasets, including developing lung epithelial cells 12 , blood monocyte/granulocyte differentiation 7 , and MAR-seq dataset for hematopoiesis 13 , recovered ordering gene sets with similar levels of overlap with the supervised selection methods ( Figure SI 1 ), confirming that dpFeature…”
Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis (2019, background): “The advent of single-cell RNA-Seq allows reliable identi ﬁ cation of even closely related cell populations (14).”
PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells (2019, neutral): “We applied PAGA to simulated data (Additional file 1: Note 5) for this system and three experimental datasets: 2730 cells measured using MARS-seq [24], 1654 cells measured using Smart-seq2 [25], and 44,802 cells from a 10× Genomics protocol [26].”
A benchmark of batch-effect correction methods for single-cell RNA sequencing data (2020, methodology): “The two data batches of this dataset were acquired by Nestorowa et al. [44] using the SMART-seq2 protocol (GSE81682, 1920 cells), and Paul et al. [45] using the MARS-seq protocol (GSE72857, 10,368 cells).”