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Transcriptome assembly and isoform expression level estimation from biased RNA-Seq reads

Wei Li, Tao Jiang
2012 Computer applications in the biosciences : CABIOS  
Our experimental results on simulated and real RNA-Seq datasets exhibit interesting effects of RNA-Seq biases on both transcriptome assembly and isoform expression level estimation.  ...  However, RNA-Seq reads are usually not uniformly distributed and biases in RNA-Seq data post great challenges in many applications including transcriptome assembly and the expression level estimation of  ...  and real RNA-Seq experiments and analyze the effects of RNA-Seq biases on both transcriptome assembly and isoform abundance level estimation.  ... 
doi:10.1093/bioinformatics/bts559 pmid:23060617 pmcid:PMC3496342 fatcat:lv6v3rk2rrelzp6jtqbenansui

Computationally efficient assembly of a Pseudomonas aeruginosa gene expression compendium [article]

Georgia Doing, Alexandra J Lee, Samuel L. Neff, Jacob D. Holt, Bruce A. Stanton, Casey S Greene, Deborah A. Hogan
2022 bioRxiv   pre-print
Finally, annotations are programmatically collected for those samples with sufficient meta-data and expression-based metrics are used to further enhance strain assignment for each sample.  ...  In this workflow, P. aeruginosa RNA-seq data are filtered using technically and biologically driven criteria with characteristics tailored to bacterial gene expression and that account for the effects  ...  Percentile cutoffs were based on visual inspection and the removal of datasets with technical differences (meta-transcriptomic data and RIP-seq data).  ... 
doi:10.1101/2022.01.24.477642 fatcat:etgioe6lbrd47dzdqe5yawvtnm

Bermuda: Bidirectional de novo assembly of transcripts with new insights for handling uneven coverage [article]

Qingming Tang, Sheng Wang, Jian Peng, Jianzhu Ma, Jinbo Xu
2015 arXiv   pre-print
Motivation: RNA-seq has made feasible the analysis of a whole set of expressed mRNAs. Mapping-based assembly of RNA-seq reads sometimes is infeasible due to lack of high-quality references.  ...  Existing methods either apply de Bruijn graphs of single-sized k-mers to assemble the full set of transcripts, or conduct multiple runs of assembly, but still apply graphs of single-sized k-mers at each  ...  This work was financially supported by the National Science Foundation CAREER award (to JX) and the Alfred P. Sloan Fel-lowship (to JX). Conflict of interest statement. None declared.  ... 
arXiv:1506.05538v1 fatcat:24lv5go2j5hkhdkmbaqiifuyem

Modeling and analysis of RNA-seq data: a review from a statistical perspective

Wei Vivian Li, Jingyi Jessica Li
2018 Quantitative Biology  
The analysis of RNA-seq data at four different levels (samples, genes, transcripts, and exons) involve multiple statistical and computational questions, some of which remain challenging up to date.  ...  We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective.  ...  Hence, j 's are estimated based on the bias-corrected estimatesl s 's.  ... 
doi:10.1007/s40484-018-0144-7 pmid:31456901 pmcid:PMC6711375 fatcat:qd2ssgwzgrdw5gm5gkueayvf3i

Single-Cell Transcriptomics: Current Methods and Challenges in Data Acquisition and Analysis

Asif Adil, Vijay Kumar, Arif Tasleem Jan, Mohammed Asger
2021 Frontiers in Neuroscience  
Single-cell transcriptomics [single-cell RNA sequencing (SC-RNA-seq)] has an immense potential of uncovering the novel basis of human life.  ...  However, due to low starting materials, the SC-RNA-seq data face various computational challenges: normalization, differential gene expression analysis, dimensionality reduction, etc.  ...  Transcriptome reconstruction can be either de novo (for samples lacking reference genome) or reference based, also called genome-guided assembly (Chen et al., 2011) .  ... 
doi:10.3389/fnins.2021.591122 pmid:33967674 pmcid:PMC8100238 fatcat:j3lku54jkrcwne2fag2g7vv5qi

Bioinformatics for RNA‐Seq Data Analysis [chapter]

Shanrong Zhao, Baohong Zhang, Ying Zhang, William Gordon, Sarah Du, Theresa Paradis, Michael Vincent, David von Schack
2016 Bioinformatics - Updated Features and Applications  
While RNA sequencing (RNA-seq) has become increasingly popular for transcriptome profiling, the analysis of the massive amount of data generated by large-scale RNA-seq still remains a challenge.  ...  In the meantime, RNA-seq is evolving rapidly, and newer sequencing technologies are briefly introduced, including stranded RNA-seq, targeted RNA-seq, and single-cell RNA-seq. approaches using shotgun sequencing  ...  Thus, RNA-seq delivers both less biased and previously unknown information about the transcriptome.  ... 
doi:10.5772/63267 fatcat:vud46vhdijalflsj3ktawkvhse

Modeling and analysis of RNA-seq data: a review from a statistical perspective [article]

Wei Vivian Li, Jingyi Jessica Li
2018 arXiv   pre-print
The analysis of RNA-seq data at four different levels (samples, genes, transcripts, and exons) involve multiple statistical and computational questions, some of which remain challenging up to date.  ...  Since the invention of next-generation RNA sequencing (RNA-seq) technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized  ...  We suggest that users consider their preferences on the precision and recall rates in discovery problems, and to evaluate the assumptions of different methods for RNA-seq read generation and bias correction  ... 
arXiv:1804.06050v3 fatcat:6sif3ufg3vgnpd53kccdzxerqy

Exploring Additional Valuable Information From Single-Cell RNA-Seq Data

Yunjin Li, Qiyue Xu, Duojiao Wu, Geng Chen
2020 Frontiers in Cell and Developmental Biology  
based on single-cell transcriptomics data.  ...  Additionally, we survey the integration of single-cell and bulk RNA-seq datasets for deconvoluting the cell composition of large-scale bulk samples and linking single-cell signatures to patient outcomes  ...  Moreover, novel SNV calling methods that are specifically designed for scRNA-seq are also crucial for correcting the technical bias and increase the sensitivity and specificity of variant calling.  ... 
doi:10.3389/fcell.2020.593007 pmid:33335900 pmcid:PMC7736616 fatcat:wbboyh6gjjbvxbutsmtmv53ztq

MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples

Jonas Behr, André Kahles, Yi Zhong, Vipin T. Sreedharan, Philipp Drewe, Gunnar Rätsch
2013 Computer applications in the biosciences : CABIOS  
It is designed for genome-and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data.  ...  Moreover, MITIE yields substantial performance gains when used with multiple samples.  ...  Funding: German Research Foundation (grants RA1894/1-1 and RA1894/2-1), the Sloan-Kettering Institute and the Max Planck Society. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btt442 pmid:23980025 pmcid:PMC3789545 fatcat:lgsvgscaevblhnuqmcs236iofm

RNA-Seq Data: A Complexity Journey

Enrico Capobianco
2014 Computational and Structural Biotechnology Journal  
expression of genes and non-coding RNAs.  ...  Since the appearance of the ENCODE project and due to follow-up work, a shift from the pervasive transcription observed from RNA-Seq data to its functional validation is gradually occurring.  ...  The author is also grateful to three reviewers and to the Editor for their remarks and suggestions, which led to an improved paper.  ... 
doi:10.1016/j.csbj.2014.09.004 pmid:25408846 pmcid:PMC4232570 fatcat:znwwul6f5jhhffd73lry2apo6u

Deep Parallel Characterization of AAV Tropism and AAV-Mediated Transcriptional Changes via Single-Cell RNA Sequencing

David Brown, Michael Altermatt, Tatyana Dobreva, Sisi Chen, Alexander Wang, Matt Thomson, Viviana Gradinaru
2021 Frontiers in Immunology  
To fully leverage the output of these large screening paradigms across multiple targets, we have developed an experimental and computational single-cell RNA sequencing (scRNA-seq) pipeline for in vivo  ...  Transcriptomic analysis revealed that this neuronal bias is due mainly to increased targeting efficiency for glutamatergic neurons, which we confirmed by RNA fluorescence in situ hybridization.  ...  Figures 1, 2, and Supplemental Figures 1, 2 , and 4 were partially created with Biorender.com.  ... 
doi:10.3389/fimmu.2021.730825 pmid:34759919 pmcid:PMC8574206 fatcat:rjategb455gwvm6vnn6m76g7bm

Proper Read Filtering Method to Adequately Analyze Whole-Transcriptome Sequencing and RNA Based Immune Repertoire Sequencing Data for Tumor Milieu Research

Sungyoung Lee, Seulki Song, Sung-Soo Yoon, Youngil Koh, Hongseok Yun
2020 Cancers  
We assessed the diversity of the TCR repertoire results from the paired WTS and IR-seq data of 31 multiple myeloma (MM) patients.  ...  Second, although IR-seq could reflect a wider TCR region with a higher capture rate than WTS, an adequate comparison with the removal of unwanted bias from potential sequencing errors was possible only  ...  The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of 1103-004-353.  ... 
doi:10.3390/cancers12123693 pmid:33317041 fatcat:fc4oryd24vfsjbkgr4fbbmge3i

A Primer for Single-Cell Sequencing in Non-Model Organisms

James M. Alfieri, Guosong Wang, Michelle M. Jonika, Clare A. Gill, Heath Blackmon, Giridhar N. Athrey
2022 Genes  
Single-cell sequencing technologies have led to a revolution in our knowledge of the diversity of cell types, connections between biological levels of organization, and relationships between genotype and  ...  Importantly, single-cell sequencing, when further applied in non-model organisms, will allow for a deeper understanding of the mechanisms between genotype and phenotype and the basis for biological variation  ...  Single cell multiple displacement amplification was developed alongside a bioinformatic approach, SCcaller, which further corrects for amplification bias and can yield genome wide average coverage of ~  ... 
doi:10.3390/genes13020380 pmid:35205423 pmcid:PMC8872538 fatcat:mzvnpaxdfjdvljbhve7q464ywm

Eleven grand challenges in single-cell data science

David Lähnemann, Johannes Köster, Ewa Szczurek, Davis J. McCarthy, Stephanie C. Hicks, Mark D. Robinson, Catalina A. Vallejos, Kieran R. Campbell, Niko Beerenwinkel, Ahmed Mahfouz, Luca Pinello, Pavel Skums (+39 others)
2020 Genome Biology  
This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.  ...  For each challenge, we highlight motivating research questions, review prior work, and formulate open problems.  ...  ") and scRNA-seq ("Challenge I: Handling sparsity in single-cell RNA sequencing").  ... 
doi:10.1186/s13059-020-1926-6 pmid:32033589 pmcid:PMC7007675 fatcat:cebolwlnmfbh3fdyrq75kgbrm4

Deep parallel characterization of AAV tropism and AAV-mediated transcriptional changes via single-cell RNA sequencing [article]

David Brown, Michael Altermatt, Tatyana Dobreva, Sisi Chen, Alexander Wang, Matt Thomson, Viviana Gradinaru
2021 bioRxiv   pre-print
To fully leverage the output of these large screening paradigms across multiple targets, we have developed an experimental and computational single-cell RNA sequencing (scRNA-seq) pipeline for in vivo  ...  Our transcriptomic analysis revealed that this neuronal bias is mainly due to increased targeting efficiency for glutamatergic neurons, which we confirmed by RNA fluorescence in situ hybridization.  ...  single-cell library preparation, Min Jee Jang for help in designing probes and troubleshooting FISH-HCR, and Ben Deverman and Ken Chan for early discussions on strategy.  ... 
doi:10.1101/2021.06.25.449955 fatcat:ale6oulvcvfxpgdwipl7qs2jsa
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