scispace - formally typeset
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.
About
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.

read more

Citations
More filters
Journal ArticleDOI

Single-cell RNA sequencing in osteoarthritis.

TL;DR: In this paper , a review summarizes the microstructural changes in articular cartilage, meniscus, synovium and subchondral bone that are mainly due to crosstalk among chondrocytes, osteoblasts, fibroblasts and endothelial cells during osteoarthritis progression.
Posted ContentDOI

Lineage Commitment of Dermal Fibroblast Progenitors is Mediated by Chromatin De-Repression

TL;DR: In this article , the authors used multimodal single-cell approaches, epigenetic assays, and allografting techniques to define a DFP state and the mechanisms that govern its differentiation potential.
Posted ContentDOI

Benchmarking Algorithms for Gene Set Scoring of Single-cell ATAC-seq Data

TL;DR: In this article , the applicability and performance of RNA-seq Gene Set scoring (GSS) tools on scATAC-seq data remain to be investigated, and the impact of gene activity conversion, dropout imputation, and gene set collections on the results of GSS is evaluated.
References
More filters
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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Related Papers (5)