Topics

Machine learning predicts putative haematopoietic stem cells within large single-cell transcriptomics datasets.

08:00 EDT 9th September 2019 | BioPortfolio

Summary of "Machine learning predicts putative haematopoietic stem cells within large single-cell transcriptomics datasets."

Haematopoietic stem cells (HSCs) are an essential source and reservoir for normal haematopoiesis, and their function is compromised in many blood disorders. HSC research has benefitted from the recent development of single-cell molecular profiling technologies, where single-cell RNA-sequencing (scRNA-seq) in particular has rapidly become an established method to profile HSCs and related haematopoietic populations. The classical definition of HSCs relies on transplantation assays, which have been used to validate HSC function for cell populations defined by flow cytometry. Flow cytometry information for single cells however is not available for many new high-throughput scRNA-seq methods, thus highlighting an urgent need for the establishment of alternative ways to pinpoint the likely HSCs within large scRNA-seq datasets. To address this, we tested a range of machine learning approaches and developed a tool, hscScore, to score single-cell transcriptomes from murine bone marrow based on their similarity to gene expression profiles of validated HSCs. We evaluated hscScore across scRNA-seq data from different laboratories, which allowed us to establish a robust method that functions across different technologies. To facilitate broad adoption of hscScore by the wider haematopoiesis community, we have made the trained model and example code freely available online. In summary, our method hscScore provides fast identification of mouse bone marrow HSCs from scRNA-seq measurements and represents a broadly useful tool for analysis of single-cell gene expression data.

Affiliation

Journal Details

This article was published in the following journal.

Name: Experimental hematology
ISSN: 1873-2399
Pages:

Links

DeepDyve research library

PubMed Articles [21838 Associated PubMed Articles listed on BioPortfolio]

Artificial Neural Network: Understanding the Basic Concepts without Mathematics.

Machine learning is where a machine (i.e., computer) determines for itself how input data is processed and predicts outcomes when provided with new data. An artificial neural network is a machine lear...

S1PR5 regulates NK cell responses in preventing graft-versus-host disease while preserving graft-versus-tumour activity in a murine allogeneic haematopoietic stem cell transplantation model.

Graft-versus-host disease (GVHD) remains a major complication following allogeneic haematopoietic stem cell transplantation (allo-HSCT) leading to high transplant-related mortality. NK cells have been...

What Is Machine Learning: a Primer for the Epidemiologist.

Machine learning is a branch of computer science that has the potential to transform epidemiological sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problem...

Primer on machine learning: utilization of large data set analyses to individualize pain management.

Pain researchers and clinicians increasingly encounter machine learning algorithms in both research methods and clinical practice. This review provides a summary of key machine learning principles, as...

Machine Learning for the Interventional Radiologist.

The purpose of this article is to describe key potential areas of application of machine learning in interventional radiology. Machine learning, although in the early stages of development within the...

Clinical Trials [11312 Associated Clinical Trials listed on BioPortfolio]

Pilot Study of Reduced Intensity Haematopoietic Stem Cell Transplantation in Patients With Poor Risk Myelodysplastic Syndrome (MDS) and Acute Myeloid Leukaemia (AML) Utilising Conditioning With Fludarabine, Busulphan and Thymoglobulin

The purpose of this study is to determine the safety and feasibility of conditioning with fludarabine, busulphan and thymoglobuline in patients with myelodysplastic syndrome (MDS), myelody...

The Effect of Mobilized Stem Cell by G-CSF and VEGF Gene Therapy in Patients With Stable Severe Angina Pectoris

The aim of this study was to evaluate the mobilization of non-haematopoietic mesenchymal and haematopoietic stem cells from the bone marrow with granulocyte colony stimulating factor (G-CS...

Safety Study of ADV-specific T-cells in Paediatric Patients Post Allo-HSCT

Human Adenovirus-specific T-cells can persist and augment impaired adenovirus immune response post allogeneic haematopoietic stem cell transplant, and reduce the requirement for antiviral ...

Stem Cell Collection

This study is designed for the collection of stem cells from the bloodstream for use in research studies. These cells will be studied to determine if they have unique features particular t...

Preventing Stem Cell Transplant Complications With a Blood Separator Machine

Background: - Researchers are working to make stem cell transplant procedures safer and more effective. One complication of transplants is graft-versus-host disease (GVHD). This complicat...

Medical and Biotech [MESH] Definitions

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.

A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.

SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.

A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.

Specialized stem cells that are committed to give rise to cells that have a particular function; examples are MYOBLASTS; MYELOID PROGENITOR CELLS; and skin stem cells. (Stem Cells: A Primer [Internet]. Bethesda (MD): National Institutes of Health (US); 2000 May [cited 2002 Apr 5]. Available from: http://www.nih.gov/news/stemcell/primer.htm)

Quick Search


DeepDyve research library

Relevant Topics

Stem Cells
Track and monitor developments in stem cell research and commercial development.  Follow the tabs above to read the latest global news, research, clinical trials on stem cells and follow companies active in the stem cell industry.  BioPort...

DNA sequencing
DNA sequencing is the process of determining the precise order of nucleotides within a DNA molecule. During DNA sequencing, the bases of a small fragment of DNA are sequentially identified from signals emitted as each fragment is re-synthesized from a ...


Searches Linking to this Article