scholarly journals Single Cell Insights Into Cancer Transcriptomes: A Five-Part Single-Cell RNAseq Case Study Lesson

CourseSource ◽  
2021 ◽  
Vol 8 ◽  
Author(s):  
Leigh Ann Samsa ◽  
Melissa Eslinger ◽  
Adam Kleinschmit ◽  
Amanda Solem ◽  
Carlos C. Goller
Keyword(s):  
Single Cell ◽  
Study Lesson

scholarly journals Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data

2020 ◽  
Author(s):  
Junpeng Zhang ◽  
Lin Liu ◽  
Taosheng Xu ◽  
Wu Zhang ◽  
Chunwen Zhao ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Single Cells ◽  
Small Scale ◽  
Mirna Regulation ◽  
Sequencing Data ◽  
Resolution Level ◽  
Novel Strategy ◽  
Cell Cell

AbstractBackgroundExisting computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation.ResultsIn this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to use single-cell miRNA-mRNA co-sequencing data to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks to understand miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. Finally, through exploring cell-cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells to help understand cell-cell crosstalk.ConclusionsTo the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation.

scholarly journals Single-cell Protein and Single-cell Oil Production from Agro-industrial By-products

2020 ◽  
Author(s):  
◽  
Krišs Spalviņš
Keyword(s):  
Single Cell ◽  
Raw Materials ◽  
Cell Protein ◽  
Fish Feed ◽  
Feed Ingredients ◽  
Fish Feeds ◽  
Aquaculture Industry ◽  
Fish And Shellfish ◽  
By Products

The aquaculture industry has been the fastest growing food production industry in the world for the last 25 years. In turn, wild capture has been stagnant for the last 20 years. As a result, in 2014 the aquaculture industry outpaced wild capture and today most fish and shellfish products are farmed in aquaculture rather than caught. Although aquaculture has a number of advantages over wild capture, the rapid development of aquaculture has led to a shortage of fish feeds. The aquaculture industry has tried to solve the feed shortage by replacing traditional feed ingredients with ones derived from agriculture, but this solution is inappropriate because plant-based ingredients are not suitable for the intestinal tract of farmed carnivorous fish, they lack several essential amino acids, and vegetable fats do not contain Omega-3 fatty acids essential in human diet. Therefore, it is necessary to find new raw materials that are suitable for use in fish feed, do not create additional burdens on the environment as wild capture and agriculture do, and also ensure that fish products fed with new raw materials are healthy for human consumption. The most suitable ingredients for these requirements are single-cell proteins (SCP) and single-cell oils (SCO). SCP and SCO are derived from microorganisms that are able to produce large amounts of proteins or oils in their cells. Currently, SCP and SCO production technologies are already used to produce high value-added products, such as pharmaceuticals, building-block chemicals, baby food, etc. However, these technologies involve the cultivation of the relevant microorganisms using refined sugars, which are relatively expensive and the use of such raw materials in the production of fish feed is not competitive. Therefore, in order to implement SCP and SCO technologies in the production of fish feeds, it is necessary to find cheap raw materials for the cultivation of microorganisms. The most suitable raw materials for the cultivation of microorganisms are biodegradable by-products of various industries. The aim of the work is to analyse the most suitable by-products for the cultivation of SCP and SCO producing microorganisms. The analysis includes: (1) literature analysis on all suitable by-products, describing the characteristics, availability and reported SCP and SCO yields when using by-products as substrates; (2) the development of a by-product supply optimization model and a case study for one by-product using the developed model; (3) creation of a laboratory stand for practical experiments; (4) experiment where SCP is produced from a previously unexplored by-product and a microorganism strain combination. The dissertation is created as a set of publications, which combines parts of scientific publications written during doctoral studies. The introduction to the work describes the aims and tasks of the work, as well as a description of scientific and practical significance. The first chapter describes the current situation in the aquaculture industry, the causes of fish feed shortages, possible solutions and the rationale for the production of SCP and SCO from by-products as the best alternative for the production of fish feed ingredients. The second chapter reviews the by-products that are suitable for the production of SCP and SCO, as well as describes the development of a by-product procurement model and a case study. The third chapter describes the creation of a laboratory stand. The fourth chapter describes practical experiments for obtaining SCP from waste cooking oil. At the end of the work, conclusions are made and recommendations are given.

scholarly journals A case study on the detailed reproducibility of a human cell atlas project

2018 ◽  
Author(s):  
Kui Hua ◽  
Xuegong Zhang
Keyword(s):  
Single Cell ◽  
Human Cell ◽  
Scientific Discovery ◽  
Cell Types ◽  
The Future ◽  
Reproduction Study ◽  
High Flexibility ◽  
Cell Data ◽  
Different Levels

AbstractReproducibility is a defining feature of a scientific discovery. Reproducibility can be at different levels for different types of study. The purpose of the Human Cell Atlas (HCA) project is to build maps of molecular signatures of all human cell types and states to serve as references for future discoveries. Constructing such a complex reference atlas must involve the assembly and aggregation of data from multiple labs, probably generated with different technologies. It has much higher requirements on reproducibility than individual research projects. To add another layer of complexity, the bioinformatics procedures involved for single-cell data have high flexibility and diversity. There are many factors in the processing and analysis of single-cell RNA-seq data that can shape the final results in different ways. To study what levels of reproducibility can be reached in current practices, we conducted a detailed reproduction study for a well-documented recent publication on the atlas of human blood dendritic cells as an example to break down the bioinformatics steps and factors that are crucial for the reproducibility at different levels. We found that the major scientific discovery can be well reproduced after some efforts, but there are also some differences in some details that may cause uncertainty in the future reference. This study provides a detailed case observation on the on-going discussions of the type of standards the HCA community should take when releasing data and publications to guarantee the reproducibility and reliability of the future atlas.

scholarly journals Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics

2019 ◽  
Vol 91 (9) ◽  
pp. 5768-5776 ◽  
Author(s):  
Zhichao Liu ◽  
Erika P. Portero ◽  
Yiren Jian ◽  
Yunjie Zhao ◽  
Rosemary M. Onjiko ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Single Cell ◽  
Cell Metabolomics

WHAT LESSON OBSERVATION DATA REVEAL ABOUT THE CHANGES IN TEACHING SCIENCE: CASE STUDY FROM LATVIA

2015 ◽  
Author(s):  
Liga Cakane ◽  
◽  
Jelena Volkinsteine ◽  
Dace Namsone ◽  
Ilze France ◽  
...  
Keyword(s):  
Education Policy ◽  
Paradigm Shift ◽  
Teaching And Learning ◽  
Teaching Quality ◽  
Observation Data ◽  
Science Teaching And Learning ◽  
Study Lesson ◽  
Research Questions ◽  
Lesson Observation

The improvement of teaching quality in Science subjects is closely connected to the implementation of reforms initiated in education policy resolutions in the school practice. It is crucial for teachers to implement the paradigm shift from transmitting information to 21st century learning design. It means to change not only teaching strategies but also their views what teaching is. Lesson observations were the main source to answer the research questions: What do lesson observations reveal about the students’ learning in science lessons according to criteria selected? What information lesson observation gives about teachers’ skills to organize learning according to changes envisaged in education policy resolutions? Key words: case study, lesson observation, science teaching and learning.

Single-cell PCR amplification of thecate dinoflagellates: a case study of Tripos (Dinophyceae)

2017 ◽  
Vol 30 (2) ◽  
pp. 1117-1124
Author(s):  
A. Hernández-Rosas ◽  
M. E. Meave del Castillo ◽  
J. Díaz-Larrea ◽  
F. Rodríguez
Keyword(s):  
Single Cell ◽  
Pcr Amplification ◽  
Single Cell Pcr

scholarly journals Normalizing single-cell RNA sequencing data with internal spike-in-like genes

2020 ◽  
Author(s):  
Li Lin ◽  
Minfang Song ◽  
Yong Jiang ◽  
Xiaojing Zhao ◽  
Haopeng Wang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Sequencing Depth ◽  
Sequencing Data ◽  
Crucial Step ◽  
Single Cell Rna Sequencing ◽  
Whole Transcriptome

ABSTRACTNormalization with respect to sequencing depth is a crucial step in single-cell RNA sequencing preprocessing. Most methods normalize data using the whole transcriptome based on the assumption that the majority of transcriptome remains constant and are unable to detect drastic changes of the transcriptome. Here, we develop an algorithm based on a small fraction of constantly expressed genes as internal spike-ins to normalize single cell RNA sequencing data. We demonstrate that the transcriptome of single cells may undergo drastic changes in several case study datasets and accounting for such heterogeneity by ISnorm improves the performance of downstream analyzes.

scholarly journals Sincell: Bioconductor package for the statistical assessment of cell-state hierarchies from single-cell RNA-seq data

2015 ◽  
Author(s):  
Miguel Juliá ◽  
Amalio Telenti ◽  
Antonio Rausell
Keyword(s):  
Single Cell ◽  
R Package ◽  
Intermediate Cell ◽  
Bioconductor Package ◽  
Rna Seq ◽  
Cell State ◽  
Describing Functions ◽  
Statistical Support ◽  
Cell Data

Summary: Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell-states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general framework composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework. Furthermore, Sincell contributes new algo-rithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies. Sincell functionalities are illustrated in a real case study where its ability to discriminate noisy from stable cell-state hierarchies is demonstrated. Availability and implementation: Sincell is an open-source R/Bioconductor package available at http://bioconductor.org/packages/3.1/bioc/html/sincell.html. A detailed vignette describing functions and workflows is provided with the package.

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