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Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models

Andrea Rau, Cathy Maugis-Rabusseau, Marie-Laure Martin-Magniette, Gilles Celeux
2015 Computer applications in the biosciences : CABIOS  
Motivation: In recent years, gene expression studies have increasingly made use of high-throughput sequencing technology.  ...  A set of simulation studies also compares the performance of the proposed model with that of several related approaches developed to cluster RNA-seq or serial analysis of gene expression data.  ...  Funding A.R. was funded as a postdoctoral researcher at Inria Saclay -Iˆle-de-France for a portion of this work. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btu845 pmid:25563332 fatcat:5qojx7ctzjet7chsjghrevewy4

A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data

Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
2019 BMC Bioinformatics  
Results: A mixture of multivariate Poisson-log normal (MPLN) model is developed for clustering of high-throughput transcriptome sequencing data.  ...  High-dimensional data of discrete and skewed nature is commonly encountered in high-throughput sequencing studies.  ...  Marcelo Ponce at the SciNet HPC Consortium, University of Toronto, M5G 0A3, Toronto, Canada. The authors thank the editorial staff for help to format the manuscript.  ... 
doi:10.1186/s12859-019-2916-0 fatcat:pye6ro6cmncbzfqkf2ymuiacou

Statistical and machine learning methods for spatially resolved transcriptomics data analysis

Zexian Zeng, Yawei Li, Yiming Li, Yuan Luo
2022 Genome Biology  
Furthermore, with the continuous evolution of sequencing protocols, the underlying assumptions of current analytical methods need to be re-evaluated and adjusted to harness the increasing data complexity  ...  To motivate and aid future model development, we herein review the recent development of statistical and machine learning methods in spatial transcriptomics, summarize useful resources, and highlight the  ...  With the advent of sequencing protocols for both scRNA-seq and spatial transcriptomics, more high-throughput data are being generated.  ... 
doi:10.1186/s13059-022-02653-7 pmid:35337374 pmcid:PMC8951701 fatcat:d7qddix4tjfppi265o7wilph5i

Single-cell Transcriptome Study as Big Data

Pingjian Yu, Wei Lin
2016 Genomics, Proteomics & Bioinformatics  
The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis.  ...  After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and  ...  Kim and Marioni [32] use a mixture of two Poisson distributions to model theoretical kinetics for 'bursty' gene expression.  ... 
doi:10.1016/j.gpb.2016.01.005 pmid:26876720 pmcid:PMC4792842 fatcat:g6zc5bsl4vhynhimaxpoi3tatq

A Multivariate Poisson-Log Normal Mixture Model for Clustering Transcriptome Sequencing Data [article]

Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
2017 arXiv   pre-print
A mixture of multivariate Poisson-Log Normal (MPLN) model is proposed for clustering of high-throughput transcriptome sequencing data.  ...  High-dimensional data of discrete and skewed nature is commonly encountered in high-throughput sequencing studies.  ...  Marcelo Ponce at the SciNet HPC Consortium, University of Toronto, ON, Canada.  ... 
arXiv:1711.11190v1 fatcat:u4ible5bvjh6ridej6xu3zzvva

RNA Sequencing and Analysis

Kimberly R. Kukurba, Stephen B. Montgomery
2015 Cold Spring Harbor Protocols  
Department of Defense, and S.B.M. is funded by the Edward Mallinckrodt, Jr. Foundation.  ...  The development of high-throughput next-generation sequencing (NGS) has revolutionized transcriptomics by enabling RNA analysis through the sequencing of complementary DNA (cDNA) ).  ...  TRANSCRIPTOME SEQUENCING The introduction of high-throughput next-generation sequencing (NGS) technologies revolutionized transcriptomics.  ... 
doi:10.1101/pdb.top084970 pmid:25870306 pmcid:PMC4863231 fatcat:iqwyhy37jrh5bmrfw4wjukraja

Mapping and differential expression analysis from short-read RNA-Seq data in model organisms

Qiong-Yi Zhao, Jacob Gratten, Restuadi Restuadi, Xuan Li
2016 Quantitative Biology  
For model organisms with a reference genome, the first step in analysis of RNA-Seq data involves mapping of short-read sequences to the reference genome.  ...  Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies.  ...  This article does not contain any studies with human or animal subjects performed by any of the authors.  ... 
doi:10.1007/s40484-016-0060-7 fatcat:idomdo4pdjgr3o7jvz44w2uxlu

Robust decomposition of cell type mixtures in spatial transcriptomics [article]

Dylan M. Cable, Evan Murray, Luli S. Zou, Aleksandrina Goeva, Evan Z. Macosko, Fei Chen, Rafael A. Irizarry
2020 bioRxiv   pre-print
mixtures, such as those observed in spatial transcriptomic technologies.  ...  Spatial transcriptomic technologies measure gene expression at increasing spatial resolution, approaching individual cells.  ...  Acknowledgements We thank Robert Stickels for providing valuable input on the analysis. We thank members of the Chen lab, Irizarry lab, and Macosko lab for helpful discussions.  ... 
doi:10.1101/2020.05.07.082750 fatcat:57rwxfgamrbgxkzi3kl67gcdmi

Computational analysis of bacterial RNA-Seq data

Ryan McClure, Divya Balasubramanian, Yan Sun, Maksym Bobrovskyy, Paul Sumby, Caroline A. Genco, Carin K. Vanderpool, Brian Tjaden
2013 Nucleic Acids Research  
Recent advances in high-throughput RNA sequencing (RNA-seq) have enabled tremendous leaps forward in our understanding of bacterial transcriptomes.  ...  However, computational methods for analysis of bacterial transcriptome data have not kept pace with the large and growing data sets generated by RNA-seq technology.  ...  Conflict of interest statement. None declared.  ... 
doi:10.1093/nar/gkt444 pmid:23716638 pmcid:PMC3737546 fatcat:uuhvcvvk7nawpoaei2vtnmfije

Single Cell RNA Sequencing of Rare Immune Cell Populations

Akira Nguyen, Weng Hua Khoo, Imogen Moran, Peter I. Croucher, Tri Giang Phan
2018 Frontiers in Immunology  
Technologies for the capture, sequencing, and bioinformatic analysis of single cells are rapidly improving, and scRNA-Seq is now becoming much more accessible to non-specialized laboratories.  ...  Single-cell RNA sequencing (scRNA-Seq) is transforming our ability to characterize cells, particularly rare cells that are often overlooked in bulk population analytical approaches.  ...  SCDE operates on a mixture of Poisson distributions to estimate error, dropouts, amplification biases, and negative binomial distributions to model detected transcripts.  ... 
doi:10.3389/fimmu.2018.01553 pmid:30022984 pmcid:PMC6039576 fatcat:q2dm53vyxbcvdfmm2pfyjagofm

Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes

Chuan Ku, Arnau Sebé-Pedrós
2019 Philosophical Transactions of the Royal Society of London. Biological Sciences  
Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology.  ...  Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches.  ...  data (e.g. with MetaCell analysis [84] ).  ... 
doi:10.1098/rstb.2019.0098 pmid:31587645 pmcid:PMC6792447 fatcat:fhr7dcmmare2zgng3lp3h7pme4

Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges

Samarendra Das, Anil Rai, Shesh N. Rai
2022 Entropy  
With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the expression dynamics of genes at the single-cell level.  ...  Differential expression analysis is the primary downstream analysis of such data to identify gene markers for cell type detection and also provide inputs to other secondary analyses.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e24070995 pmid:35885218 pmcid:PMC9315519 fatcat:aimn6wxl7nbdtdmqpok4fg5fm4

Computational Oncology in the Multi-Omics Era: State of the Art

Guillermo de Anda-Jáuregui, Enrique Hernández-Lemus
2020 Frontiers in Oncology  
We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings  ...  ; classification, diagnosis, and prognosis; and the development of models in the research setting, including their use for therapeutic target identification.  ...  Tools, such as CellProfiler (157) allow for a high-throughput analysis of data.  ... 
doi:10.3389/fonc.2020.00423 pmid:32318338 pmcid:PMC7154096 fatcat:lrlg3yyo2ffkdaz2whv2egyklq

Transcriptomics for understanding marine fish larval development1This review is part of a virtual symposium on current topics in aquaculture of marine fish and shellfish

D. Mazurais, M. Darias, J.L. Zambonino-Infante, C.L. Cahu
2011 Canadian Journal of Zoology  
The development of bioinformatic resources (DNA or cDNA sequences) and molecular tools enabling high throughput gene expression analysis (microarrays) have allowed the transcriptome of marine fish species  ...  Special attention is paid to investigations of transcriptomic patterns during postembryonic development and to the impact of environmental or nutritional factors on the transcriptome of marine fish larvae  ...  combined with transcriptomic analysis.  ... 
doi:10.1139/z11-036 fatcat:x37r5a22mba3rfranxeasigdgu

Nonparametric clustering of RNA-sequencing data [article]

Gabriel Lozano, Nadia Atallah, Michael Levine
2022 arXiv   pre-print
Identification of clusters of co-expressed genes in transcriptomic data is a difficult task.  ...  This algorithm was proposed earlier in statistical literature but has not been, to the best of our knowledge, applied to transcriptomics data.  ...  Introduction Increasingly complex studies of transcriptome dynamics can be carried out now using high-throughput sequencing of reverse-transcribed RNA molecules.  ... 
arXiv:2209.11705v1 fatcat:nie3wuiijzfalfqrohbpjr6cfu
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