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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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Genome-Wide Analysis of Yeast Metabolic Cycle through Metabolic Network Models Reveals Superiority of Integrated ATAC-seq Data over RNA-seq Data

TL;DR: The preliminary results showed that epigenomic data sets can pave the way for more accurate metabolic simulations, and it is proposed that the incorporation of epigenetic information is a promising approach in the accurate prediction of metabolic dynamics.
Journal ArticleDOI

Modeling genetic platelet disorders with human pluripotent stem cells: mega-progress but wanting more on our plate(let).

TL;DR: In this article, the authors reviewed recent advances in PSC-derived megakaryocyte (iMK) technology, focusing on platform validation, disease modeling and current limitations, and confirmed that iMK can recapitulate many transcriptional and functional aspects of megakocyte and platelet biology, including variables associated with complex genetic traits such as sex and race.
Journal ArticleDOI

Developmental dynamics of chromatin accessibility during post-implantation development of monkey embryos

TL;DR: In this article , a single-cell assay for transposase accessible chromatin sequencing was applied to in vitro cultured cynomolgus monkey (Macaca fascicularis, hereafter referred to as monkey) embryos to investigate the chromatin status.
Posted ContentDOI

Pathway Analysis Through Mutual Information

Gustavo S. Jeuken, +1 more
- 02 Jul 2022 - 
TL;DR: This work proposes a new method for pathway analysis, MIPath, that relies on information theoretical principles, and therefore is absent of a model for the nature of the association between pathway activity and phenotype, resulting on a very minimal set of assumptions.
Journal ArticleDOI

Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line

TL;DR: In this paper , the authors measured activity patterns across 24,844 human lymphoblastoid single cells and found that the majority of enhancers associated with the same gene display significant correlation in their chromatin profiles.
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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