scholarly journals Meeting the challenges of high-dimensional data analysis in immunology

2018 ◽  
Author(s):  
Subarna Palit ◽  
Fabian J. Theis ◽  
Christina E. Zielinski
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Immune Regulation ◽  
Cellular Heterogeneity ◽  
High Dimensionality ◽  
High Dimensional ◽  
Mass Cytometry ◽  
Analysis Techniques ◽  
The Impact ◽  
Cell Data

AbstractRecent advances in cytometry have radically altered the fate of single-cell proteomics by allowing a more accurate understanding of complex biological systems. Mass cytometry (CyTOF) provides simultaneous single-cell measurements that are crucial to understand cellular heterogeneity and identify novel cellular subsets. High-dimensional CyTOF data were traditionally analyzed by gating on bivariate dot plots, which are not only laborious given the quadratic increase of complexity with dimension but are also biased through manual gating. This review aims to discuss the impact of new analysis techniques for in-depths insights into the dynamics of immune regulation obtained from static snapshot data and to provide tools to immunologists to address the high dimensionality of their single-cell data.

scholarly journals SCOUT: Single-cell outlier analysis in cancer

2020 ◽  
Author(s):  
Giovana Ravizzoni Onzi ◽  
Juliano Luiz Faccioni ◽  
Alvaro G. Alvarado ◽  
Paula Andreghetto Bracco ◽  
Harley I. Kornblum ◽  
...  
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Biological Markers ◽  
Rna Seq ◽  
Outlier Analysis ◽  
Mass Cytometry ◽  
Wide Range ◽  
Cell Data

Outliers are often ignored or even removed from data analysis. In cancer, however, single outlier cells can be of major importance, since they have uncommon characteristics that may confer capacity to invade, metastasize, or resist to therapy. Here we present the Single-Cell OUTlier analysis (SCOUT), a resource for single-cell data analysis focusing on outlier cells, and the SCOUT Selector (SCOUTS), an application to systematically apply SCOUT on a dataset over a wide range of biological markers. Using publicly available datasets of cancer samples obtained from mass cytometry and single-cell RNA-seq platforms, outlier cells for the expression of proteins or RNAs were identified and compared to their non-outlier counterparts among different samples. Our results show that analyzing single-cell data using SCOUT can uncover key information not easily observed in the analysis of the whole population.

scholarly journals Meeting the Challenges of High-Dimensional Single-Cell Data Analysis in Immunology

2019 ◽  
Vol 10 ◽  
Author(s):  
Subarna Palit ◽  
Christoph Heuser ◽  
Gustavo P. de Almeida ◽  
Fabian J. Theis ◽  
Christina E. Zielinski
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
High Dimensional ◽  
Cell Data

scholarly journals Single-Cell Data Analysis Using MMD Variational Autoencoder for a More Informative Latent Representation

2019 ◽  
Author(s):  
Chao Zhang
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Image Data ◽  
Mass Cytometry ◽  
Multiple Perspectives ◽  
Original Dataset ◽  
Latent Space ◽  
Variational Autoencoder ◽  
Set Up ◽  
Cell Data

AbstractVariational Autoencoder (VAE) is a generative model from the computer vision community; it learns a latent representation of images and generates new images in an unsupervised way. Recently, Vanilla VAE has been applied to single-cell data analysis, in the hope of harnessing the representation power of latent space to evade the “curse of dimensionality” of the original dataset. However, Vanilla VAE is suffering from the issue of less informative latent space, which raises a question concerning the reliability of Vanilla VAE latent space in representing the high-dimensional single-cell datasets. Therefore I set up such a study to examine this issue from the multiple perspectives.This paper confirms the issue of Vanilla VAE by comparing it with MMD-VAE, a variant of VAE which has claimed to have overcome this issue based on image data, across a series of single-cell RNAseq and mass cytometry datasets. The result indicates that MMD-VAE is superior to Vanilla VAE in retaining the information not only in the latent space but also the reconstruction space, which suggests that MMD-VAE be a better option for single-cell data analysis than Vanilla VAE.

INDONESIA LANGUAGE INTERFERENCE FORM IN BASIC PPL LEARNING THAILAND UNHASY COLLEGE SYUDENTS

2020 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Siti Mariana Ulfa
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Data Collection ◽  
Teaching Practice ◽  
Data Presentation ◽  
Analysis Techniques ◽  
Thai Students ◽  
The Impact ◽  
Collection Methods ◽  
Recording Techniques

AbstractHumans on earth need social interaction with others. Humans can use more than one language in communication. Thus, the impact that arises when the use of one or more languages is the contact between languages. One obvious form of contact between languages is interference. Interference can occur at all levels of life. As in this study, namely Indonesian Language Interference in Learning PPL Basic Thailand Unhasy Students. This study contains the form of interference that occurs in Thai students who are conducting teaching practices in the classroom. This type of research is descriptive qualitative research that seeks to describe any interference that occurs in the speech of Thai students when teaching practice. Data collection methods in this study are (1) observation techniques, (2) audio-visual recording techniques using CCTV and (3) recording techniques, by recording all data that has been obtained. Whereas the data wetness uses, (1) data triangulation, (2) improvement in perseverance and (3) peer review through discussion. Data analysis techniques in this study are (1) data collection, (2) data reduction, (3) data presentation and (4) conclusions. It can be seen that the interference that occurs includes (1) interference in phonological systems, (2) interference in morphological systems and (3) interference in syntactic systems. 

scholarly journals Correction to: High-dimensional single cell mass cytometry analysis of the murine hematopoietic system reveals signatures induced by ageing and physiological pathogen challenges

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Christos Nikolaou ◽  
Kerstin Muehle ◽  
Stephan Schlickeiser ◽  
Alberto Sada Japp ◽  
Nadine Matzmohr ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Mass ◽  
High Dimensional ◽  
Mass Cytometry ◽  
Hematopoietic System

An amendment to this paper has been published and can be accessed via the original article.

scholarly journals High-throughput single cell data analysis – A tutorial

2021 ◽  
pp. 338872
Author(s):  
Gerjen H. Tinnevelt ◽  
Kristiaan Wouters ◽  
Geert J. Postma ◽  
Rita Folcarelli ◽  
Jeroen J. Jansen
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
High Throughput ◽  
Cell Data

scholarly journals Nilai Multikultural dalam Pembelajaran Pendidikan Agama Islam (PAI) di Sekolah: Studi terhadap Upaya Membina Karakter Siswa di SMKN 1 Gerung

2019 ◽  
Vol 15 (1) ◽  
pp. 66-83 ◽  
Author(s):  
Murzal Mahsun
Keyword(s):  
Data Analysis ◽  
Islamic Education ◽  
Data Display ◽  
Mutual Cooperation ◽  
Analysis Techniques ◽  
Learning Content ◽  
Collection Data ◽  
Character Building ◽  
Mutual Tolerance ◽  
The Impact

This study aims to examine three main problems, namely: multicultural values ​​contained in Islamic Education (PAI) learning; the process of investing multicultural values ​​in PAI learning; methods of character building through multicultural values ​​in PAI learning. The study was conducted at SMK 1 Gerung, West Lombok. Data analysis techniques include data collection, data reduction, data display and conclusion verification. The findings show that multicultural values ​​contained in PAI learning content include tolerance values, equality values, unity values, kinship values, and justice values. The planting of multicultural values ​​in PAI learning at SMK 1 Gerung uses two methods, namely the exemplary method and the habituation method. The impact of planting multicultural values ​​on students is the growth of mutual tolerance, respect, accepting the opinions of others, mutual cooperation, not hostile, and the absence of conflict due to differences in culture, ethnicity, language, customs, and religion. Abstrak: Penelitian ini bertujuan untuk mengkaji tiga permasalahan utama, yaitu: nilai-nilai multikultural yang terdapat dalam pembelajaran PAI; proses penanaman nilai multikultural dalam pembelajaran PAI; metode pembinaan karakter melalui nilai multikulturalal dalam pembelajaran PAI. Penelitian dilakukan di SMKN 1 Gerung. Teknik analisis data yang digunakan pada penelitian ini meliputi pengumpulan data, reduksi data, penyajian data dan penarikan kesimpulan. Hasil penelitian ini menunjukkan bahwa nilai-nilai multikultural yang terdapat dalam buku mata pelajaran Pendidikan Agama Islam meliputi nilai toleransi, nilai kesamaan, nilai persatuan, nilai kekerabatan, dan nilai keadilan. Penanaman nilai-nilai multikultural dalam pembelajaran Pendidikan Agama Islam di SMKN 1 Gerung menggunakan dua metode yaitu metode keteladanan dan metode pembiasaan. Dampak penanaman nilai-nilai multikultural terhadap siswa yaitu tumbuhnya sikap saling toleran, menghormati, menerima pendapat orang lain, saling bekerjasama, tidak bermusuhan, dan tidak adanya konflik karena perbedaan budaya, suku, bahasa, adat istiadat, dan agama.  

scholarly journals Distinguishing different modes of growth using single-cell data

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Prathitha Kar ◽  
Sriram Tiruvadi-Krishnan ◽  
Jaana Männik ◽  
Jaan Männik ◽  
Ariel Amir
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Statistical Methods ◽  
Synthetic Data ◽  
Cellular Growth ◽  
Biological Mechanisms ◽  
E Coli ◽  
High Throughput Data ◽  
Consistent Method ◽  
Cell Data

Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.

scholarly journals Dissecting alterations in human CD8+ T cells with aging by high-dimensional single cell mass cytometry

2019 ◽  
Vol 200 ◽  
pp. 24-30 ◽  
Author(s):  
Min Sun Shin ◽  
Kristina Yim ◽  
Kevin Moon ◽  
Hong-Jai Park ◽  
Subhasis Mohanty ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Cd8 T Cells ◽  
Cell Mass ◽  
High Dimensional ◽  
Mass Cytometry
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