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Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. ...
Single-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are ...
Zhang, Min Chen, and Cong Zhang at the University of Texas at Dallas, Yuxuan Liu at the University of Texas Southwestern Medical Center, Bochao Liu at Rutgers ...
doi:10.1101/827840
fatcat:evs6tx2fcrhyhobau34favszpm
Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data
[article]
2019
arXiv
pre-print
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statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. ...
Single-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are ...
Zhang, Min Chen, and Cong Zhang at the University of Texas at Dallas, Yuxuan Liu at the University of Texas Southwestern Medical Center, Bochao Liu at Rutgers ...
arXiv:1911.00356v1
fatcat:ajo44vi5izgjtoy5ebysrwswvm
A mechanistic model for the negative binomial distribution of single-cell mRNA counts
[article]
2019
bioRxiv
pre-print
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Several tools analyze the outcome of single-cell RNA-seq experiments, and they often assume a probability distribution for the observed sequencing counts. ...
Our results indicate that the negative binomial distribution arises as steady-state distribution from a mechanistic model that produces mRNA molecules in bursts. ...
Acknowledgments Our research was supported by the German Research Foundation within the SFB 1243, Subproject A17, by the German Federal Ministry of Education and Research under grant number 01DH17024, ...
doi:10.1101/657619
fatcat:2ukdcjrccrgutjtaowpx52wnju
RNA Sequencing and Analysis
2015
Cold Spring Harbor Protocols
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K.R.K. is supported by the National Defense Science and Engineering Graduate (NDSEG) Fellowship from the U.S. Department of Defense, and S.B.M. is funded by the Edward Mallinckrodt, Jr. Foundation. ...
Mauro Pala, for their valuable comments. ...
binomial distribution
DESeq
Exon-based approach using the negative binomial model
DEGSeq
Isoform-based approach using the Poisson model
EdgeR
Count-based approach using empirical Bayes method based ...
doi:10.1101/pdb.top084970
pmid:25870306
pmcid:PMC4863231
fatcat:iqwyhy37jrh5bmrfw4wjukraja
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing
2017
Bioinformatics
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Statistical analysis and the validity of conclusions drawn from (time series) 16S rRNA and other metagenomic sequencing data is hampered by the presence of significant amount of noise and missing data ...
The proposed Temporal Gaussian Process Model for Compositional Data Analysis (TGP-CODA) shows superior modeling performance compared to commonly used Dirichlet-multinomial, multinomial and non-parametric ...
This work was supported by Simons Foundation. Conflict of Interest: none declared. ...
doi:10.1093/bioinformatics/btx549
pmid:28968799
pmcid:PMC5860357
fatcat:petx735ga5c4xhu5esvpslhila
Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing
[article]
2016
bioRxiv
pre-print
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Statistical analysis and the validity of conclusions drawn from (time series) 16S rRNA and other metagenomic sequencing data is hampered by the presence of significant amount of noise and missing data ...
The proposed Temporal Gaussian Process Model for Compositional Data Analysis (TGP-CODA) shows superior modeling performance compared to commonly used Dirichlet-multinomial, multinomial, and non-parametric ...
Acknowledgements We acknowledge the computational resources provided by the computing group of Simons Center for Data Analysis. ...
doi:10.1101/076836
fatcat:lorq7uvzufegjihedgm5uplu7u
Single-cell RNA sequencing technologies and bioinformatics pipelines
2018
Experimental and Molecular Medicine
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Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in ...
In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data. ...
To account for various sources of noise in single-cell data, however, a better fit can be obtained by using a Negative Binomial model (variance = mean + over-dispersion×mean 2 ; for most genes, overdispersion ...
doi:10.1038/s12276-018-0071-8
pmid:30089861
pmcid:PMC6082860
fatcat:5hbi2tvtcrh4ble5ibj6eudjem
Chromatin accessibility dynamics of myogenesis at single cell resolution
[article]
2017
bioRxiv
pre-print
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We introduce Cicero, a statistical method that connects regulatory elements to target genes using single cell chromatin accessibility data. ...
The methodological framework described here constitutes a powerful new approach for elucidating the architecture, grammar and mechanisms of cis-regulation on a genome-wide basis. ...
Acknowledgements We gratefully acknowledge Stephen Tapscott, William Noble, and Daniela Witten as well as members of the Shendure and Trapnell labs for their advice. ...
doi:10.1101/155473
fatcat:2ocky2kwerda7kn4khxkbbbsqi
Transcriptional Programming of Normal and Inflamed Human Epidermis at Single-Cell Resolution
2018
Cell Reports
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Here we report single-cell RNA sequencing profiles of 92,889 human epidermal cells from 9 normal and 3 inflamed skin samples. ...
We also identify molecular fingerprints of inflammatory skin states, including S100 activation in the interfollicular epidermis of normal scalp, enrichment of a CD1C+CD301A+ myeloid dendritic cell population ...
This work was supported in part by funds from NIH grant R01CA163336 and the Grainger Engineering Breakthroughs
DECLARATION OF INTERESTS The authors declare no competing interests. ...
doi:10.1016/j.celrep.2018.09.006
pmid:30355494
pmcid:PMC6367716
fatcat:jqq5elx2afczhlmpyu3ci54eda
In vivo negative regulation of SARS-CoV-2 receptor, ACE2, by interferons and its genetic control
2021
Wellcome Open Research
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Negative correlation was also found in the gastrointestinal tract where inflammation driven IFN-stimulated genes were negatively correlated with ACE2 expression and in lung tissue from a murine model of ...
Angiotensin I converting enzyme 2 (ACE2) is a receptor for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and differences in its expression may affect susceptibility to infection. ...
Acknowledgements The authors would like to thank Gilead Sciences for the provision of samples and data from the BOSON clinical study for use in these analyses. ...
doi:10.12688/wellcomeopenres.16559.1
fatcat:746ykc5zmvg7vpz6hktk4lfy2q
Improved Ribosome-Footprint and mRNA Measurements Provide Insights into Dynamics and Regulation of Yeast Translation
2016
Cell Reports
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of Ribo-Zero-treated RNA compared to those measured by RNA-seq of total unselected RNA. ...
on mapped RNA-seq reads from only the 30 ends of genes (Fig-
and RNA-seq data. ...
doi:10.1016/j.celrep.2016.01.043
pmid:26876183
pmcid:PMC4767672
fatcat:ohs2tg37arc3va6hfmqbknjbjm
Improved ribosome-footprint and mRNA measurements provide insights into dynamics and regulation of yeast translation
[article]
2015
biorxiv/medrxiv
pre-print
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with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5′- untranslated regions. ...
Collectively, our results reveal key features of translational control in yeast and provide a framework for executing and interpreting ribosome- profiling studies. ...
of Ribo-Zero-treated RNA compared to those measured by RNA-seq of total unselected RNA. ...
doi:10.1101/021501
fatcat:ogb63bvmrjcvdir73qsbanvqhy
A Comprehensive Overview of Online Resources to Identify and Predict Bacterial Essential Genes
2017
Frontiers in Microbiology
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The continuous progress of experimental method for essential gene identification has accelerated the accumulation of gene essentiality data which facilitates the study of essential genes in silico. ...
Genes critical for the survival or reproduction of an organism in certain circumstances are classified as essential genes. ...
Feng-Biao Guo's laboratory for providing the standalone version of Geptop. ...
doi:10.3389/fmicb.2017.02331
pmid:29230204
pmcid:PMC5711816
fatcat:flf2b6ljnbcmbayijjemtfa56q
A quantitative and predictive model for RNA binding by human Pumilio proteins
[article]
2018
bioRxiv
pre-print
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We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2 ...
High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). ...
We thank Namita Bisaria, Greg Hogan, Julia Salzman, Erik Van Nostrand and members of the Herschlag lab for helpful discussions and comments on the manuscript. ...
doi:10.1101/403006
fatcat:6ccykl2j45ab3dte2kwz3t4qfa
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
2019
Information Fusion
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2018 pre-print arXiv:1807.00123v1 fatcat:zrpz2xp7ojgyjdq62xm23zvlmqOther Versions
No single data type, however, can capture the complexity of all the factors relevant to understanding a phenomenon such as a disease. ...
The key challenge in developing such approaches is the identification of effective models to provide a comprehensive and relevant systems view. ...
single-cell DNA methylation and single-cell RNA-seq data. ...
doi:10.1016/j.inffus.2018.09.012
pmid:30467459
pmcid:PMC6242341
fatcat:mjhnzxxv4fbrlgufb7vkg3pz5u
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