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Open AccessJournal ArticleDOI

Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis

TLDR
In this paper, the authors applied single-cell RNA sequencing (scRNA-seq) and single cell assay for transposase-accessible chromatin sequencing to over 8,000 human immunophenotypic blood cells from fetal liver and bone marrow.
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This article is published in Cell Stem Cell.The article was published on 2021-03-04 and is currently open access. It has received 122 citations till now. The article focuses on the topics: ATAC-seq & Chromatin.

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Evaluation of Ranzoni et al.: Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis.

TL;DR: In this paper, a peer review process for integrated single-cell RNA-seq and ATAC-Seq analysis of human developmental Hematopoiesis is presented. But this process is restricted to single cell RNA sequencing.
Journal ArticleDOI

High-throughput methods for the analysis of transcription factors and chromatin modifications: Low input, single cell and spatial genomic technologies.

TL;DR: In this article , a set of approaches progressively pushing the limits of epigenetic profiling towards single cells are presented. But the authors focus on single-cell and spatial genomic applications and do not discuss the benefits of using multiple TFs or histone modifications in parallel.
Journal ArticleDOI

Temporary serine protease inhibition and the role of SPINK2 in human bone marrow

TL;DR: In this paper , the SPINK2 degradation constant was determined and a mathematical relationship was derived to predict the zone of inhibited target protease activity surrounding SPINK-secreting HSPCs.
Posted ContentDOI

Postnatal lymph node expansion of stromal progenitors towards reticular and CD34+ stromal cell subsets is determined by distinct transcriptional programs

TL;DR: The tissue-specific epigenomic DNA accessibility and CpG methylation landscape of LN non-endothelial SCs is dissected and a microbiota-independent core epigenomic signature is identified, representing a valuable resource to identify core transcriptional regulators that impinge on the developing mLN early in life, thereby shaping long-lasting intestinal adaptive immune responses.
References
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Journal Article

Scikit-learn: Machine Learning in Python

TL;DR: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language.
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Deep learning

TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
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The Sequence Alignment/Map format and SAMtools

TL;DR: SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
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Fast and accurate short read alignment with Burrows–Wheeler transform

TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
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STAR: ultrafast universal RNA-seq aligner

TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
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