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Transcriptome analysis

Section edited by Adam Olshen

This section incorporates all aspects of transcriptomic analysis including but not limited to: methods and applications for the analysis of microarray and RNA-seq data.

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  1. Systematic technical effects—also called batch effects—are a considerable challenge when analyzing DNA methylation (DNAm) microarray data, because they can lead to false results when confounded with the variab...

    Authors: Tristan Zindler, Helge Frieling, Alexandra Neyazi, Stefan Bleich and Eva Friedel

    Citation: BMC Bioinformatics 2020 21:271

    Content type: Research article

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  2. Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole b...

    Authors: Raúl Aguirre-Gamboa, Niek de Klein, Jennifer di Tommaso, Annique Claringbould, Monique GP van der Wijst, Dylan de Vries, Harm Brugge, Roy Oelen, Urmo Võsa, Maria M. Zorro, Xiaojin Chu, Olivier B. Bakker, Zuzanna Borek, Isis Ricaño-Ponce, Patrick Deelen, Cheng-Jiang Xu…

    Citation: BMC Bioinformatics 2020 21:243

    Content type: Methodology article

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  3. Single-cell RNA sequencing (scRNA-seq) provides an effective tool to investigate the transcriptomic characteristics at the single-cell resolution. Due to the low amounts of transcripts in single cells and the ...

    Authors: Yang Qi, Yang Guo, Huixin Jiao and Xuequn Shang

    Citation: BMC Bioinformatics 2020 21:240

    Content type: Methodology Article

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  4. Mounting evidence suggests several diseases and biological processes target transcription termination to misregulate gene expression. Disruption of transcription termination leads to readthrough transcription ...

    Authors: Samuel J. Roth, Sven Heinz and Christopher Benner

    Citation: BMC Bioinformatics 2020 21:214

    Content type: Software

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  5. With the explosion in the number of methods designed to analyze bulk and single-cell RNA-seq data, there is a growing need for approaches that assess and compare these methods. The usual technique is to compar...

    Authors: David Gerard

    Citation: BMC Bioinformatics 2020 21:206

    Content type: Methodology Article

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  6. Circular RNAs (circRNAs) are a newly appreciated class of non-coding RNA molecules. Numerous tools have been developed for the detection of circRNAs, however computational tools to perform downstream functiona...

    Authors: Simona Aufiero, Yolan J. Reckman, Anke J. Tijsen, Yigal M. Pinto and Esther E. Creemers

    Citation: BMC Bioinformatics 2020 21:164

    Content type: Software

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  7. Microarray technology provides the expression level of many genes. Nowadays, an important issue is to select a small number of informative differentially expressed genes that provide biological knowledge and m...

    Authors: José María Martínez-Otzeta, Itziar Irigoien, Basilio Sierra and Concepción Arenas

    Citation: BMC Bioinformatics 2020 21:135

    Content type: Software

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  8. With the cost of DNA sequencing decreasing, increasing amounts of RNA-Seq data are being generated giving novel insight into gene expression and regulation. Prior to analysis of gene expression, the RNA-Seq da...

    Authors: Xiaokang Zhang and Inge Jonassen

    Citation: BMC Bioinformatics 2020 21:110

    Content type: Software

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  9. To understand biology and differences among various tissues or cell types, one typically searches for molecular features that display characteristic abundance patterns. Several specificity metrics have been in...

    Authors: Celine Everaert, Pieter-Jan Volders, Annelien Morlion, Olivier Thas and Pieter Mestdagh

    Citation: BMC Bioinformatics 2020 21:58

    Content type: Methodology article

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  10. Quality Control in any high-throughput sequencing technology is a critical step, which if overlooked can compromise an experiment and the resulting conclusions. A number of methods exist to identify biases dur...

    Authors: Gaurav Kumar, Adam Ertel, George Feldman, Joan Kupper and Paolo Fortina

    Citation: BMC Bioinformatics 2020 21:56

    Content type: Software

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  11. High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to b...

    Authors: Arran K. Turnbull, Cigdem Selli, Carlos Martinez-Perez, Anu Fernando, Lorna Renshaw, Jane Keys, Jonine D. Figueroa, Xiaping He, Maki Tanioka, Alison F. Munro, Lee Murphy, Angie Fawkes, Richard Clark, Audrey Coutts, Charles M. Perou, Lisa A. Carey…

    Citation: BMC Bioinformatics 2020 21:30

    Content type: Research article

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  12. Cell-type heterogeneity of tumors is a key factor in tumor progression and response to chemotherapy. Tumor cell-type heterogeneity, defined as the proportion of the various cell-types in a tumor, can be inferr...

    Authors: Clémentine Decamps, Florian Privé, Raphael Bacher, Daniel Jost, Arthur Waguet, Eugene Andres Houseman, Eugene Lurie, Pavlo Lutsik, Aleksandar Milosavljevic, Michael Scherer, Michael G. B. Blum and Magali Richard

    Citation: BMC Bioinformatics 2020 21:16

    Content type: Methodology article

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  13. Reactivation of the telomerase reverse transcriptase gene TERT is a central feature for unlimited proliferation of the majority of cancers. However, the underlying regulatory processes are only partly understood.

    Authors: Alexandra M. Poos, Theresa Kordaß, Amol Kolte, Volker Ast, Marcus Oswald, Karsten Rippe and Rainer König

    Citation: BMC Bioinformatics 2019 20:737

    Content type: Methodology article

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  14. Although microarray studies have greatly contributed to recent genetic advances, lack of replication has been a continuing concern in this area. Complex study designs have the potential to address this concern...

    Authors: Elham Khodayari Moez, Morteza Hajihosseini, Jeffrey L. Andrews and Irina Dinu

    Citation: BMC Bioinformatics 2019 20:650

    Content type: Methodology article

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  15. High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify ...

    Authors: Ling Zhang, Ishwor Thapa, Christian Haas and Dhundy Bastola

    Citation: BMC Bioinformatics 2019 20:601

    Content type: Methodology Article

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  16. Tea is the oldest and among the world’s most popular non-alcoholic beverages, which has important economic, health and cultural values. Tea is commonly produced from the leaves of tea plants (Camellia sinensis), ...

    Authors: Fang-Dong Li, Wei Tong, En-Hua Xia and Chao-Ling Wei

    Citation: BMC Bioinformatics 2019 20:553

    Content type: Research article

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  17. Transcriptomic data is often used to build statistical models which are predictive of a given phenotype, such as disease status. Genes work together in pathways and it is widely thought that pathway representa...

    Authors: Marcelo P. Segura-Lepe, Hector C. Keun and Timothy M. D. Ebbels

    Citation: BMC Bioinformatics 2019 20:543

    Content type: Research article

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  18. High-throughput sequencing experiments, which can determine allele origins, have been used to assess genome-wide allele-specific expression. Despite the amount of data generated from high-throughput experiment...

    Authors: Jing Xie, Tieming Ji, Marco A. R. Ferreira, Yahan Li, Bhaumik N. Patel and Rocio M. Rivera

    Citation: BMC Bioinformatics 2019 20:530

    Content type: Methodology Article

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  19. 5′-end sequencing assays, and Cap Analysis of Gene Expression (CAGE) in particular, have been instrumental in studying transcriptional regulation. 5′-end methods provide genome-wide maps of transcription start...

    Authors: Malte Thodberg, Axel Thieffry, Kristoffer Vitting-Seerup, Robin Andersson and Albin Sandelin

    Citation: BMC Bioinformatics 2019 20:487

    Content type: Software

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  20. High-throughput gene expression technologies provide complex datasets reflecting mechanisms perturbed in an experiment, typically in a treatment versus control design. Analysis of these information-rich data c...

    Authors: Florian Martin, Sylvain Gubian, Marja Talikka, Julia Hoeng and Manuel C. Peitsch

    Citation: BMC Bioinformatics 2019 20:451

    Content type: Software

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  21. The epidermal growth factor receptor (EGFR) is a major regulator of proliferation in tumor cells. Elevated expression levels of EGFR are associated with prognosis and clinical outcomes of patients in a variety...

    Authors: Claus Weinholdt, Henri Wichmann, Johanna Kotrba, David H. Ardell, Matthias Kappler, Alexander W. Eckert, Dirk Vordermark and Ivo Grosse

    Citation: BMC Bioinformatics 2019 20:434

    Content type: Research article

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  22. Ultra-fast pseudo-alignment approaches are the tool of choice in transcript-level RNA sequencing (RNA-seq) analyses. Unfortunately, these methods couple the tasks of pseudo-alignment and transcript quantificat...

    Authors: Mohamed K Gunady, Stephen M Mount and Héctor Corrada Bravo

    Citation: BMC Bioinformatics 2019 20:421

    Content type: Methodology article

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  23. Standard RNAseq methods using bulk RNA and recent single-cell RNAseq methods use DNA barcodes to identify samples and cells, and the barcoded cDNAs are pooled into a library pool before high throughput sequenc...

    Authors: Shintaro Katayama, Tiina Skoog, Cilla Söderhäll, Elisabet Einarsdottir, Kaarel Krjutškov and Juha Kere

    Citation: BMC Bioinformatics 2019 20:418

    Content type: Software

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  24. High-dimensional data of discrete and skewed nature is commonly encountered in high-throughput sequencing studies. Analyzing the network itself or the interplay between genes in this type of data continues to ...

    Authors: Anjali Silva, Steven J. Rothstein, Paul D. McNicholas and Sanjeena Subedi

    Citation: BMC Bioinformatics 2019 20:394

    Content type: Methodology article

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  25. MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In ...

    Authors: Emmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav and Malin Sund

    Citation: BMC Bioinformatics 2019 20:393

    Content type: Research article

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  26. The QuantiGene® Plex 2.0 platform (ThermoFisher Scientific) combines bDNA with the Luminex/xMAP magnetic bead capturing technology to assess differential gene expression in a compound exposure setting. This te...

    Authors: Bie Verbist, Eva Adriaensen, Vikki Keersmaekers, Dea Putri, Marjolein Crabbe, Maarten Derks, Rytis Bagdziunas, Griet Laenen and Hans De Wolf

    Citation: BMC Bioinformatics 2019 20:378

    Content type: Methodology article

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  27. Single cell RNA sequencing (scRNA-seq) brings unprecedented opportunities for mapping the heterogeneity of complex cellular environments such as bone marrow, and provides insight into many cellular processes. ...

    Authors: Sergii Domanskyi, Anthony Szedlak, Nathaniel T Hawkins, Jiayin Wang, Giovanni Paternostro and Carlo Piermarocchi

    Citation: BMC Bioinformatics 2019 20:369

    Content type: Methodology article

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  28. A microRNA (miRNA) sponge is an RNA molecule with multiple tandem miRNA response elements that can sequester miRNAs from their target mRNAs. Despite growing appreciation of the importance of miRNA sponges, our...

    Authors: Junpeng Zhang, Lin Liu, Taosheng Xu, Yong Xie, Chunwen Zhao, Jiuyong Li and Thuc Duy Le

    Citation: BMC Bioinformatics 2019 20:235

    Content type: Software

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  29. The rapid increase in High-throughput sequencing of RNA (RNA-seq) has led to tremendous improvements in the detection and reconstruction of both expressed coding and non-coding RNA transcripts. Yet, the comple...

    Authors: Thomas Gatter and Peter F Stadler

    Citation: BMC Bioinformatics 2019 20:190

    Content type: Methodology article

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  30. For many practical hypothesis testing (H-T) applications, the data are correlated and/or with heterogeneous variance structure. The regression t-test for weighted linear mixed-effects regression (LMER) is a legit...

    Authors: Yun Zhang, Gautam Bandyopadhyay, David J. Topham, Ann R. Falsey and Xing Qiu

    Citation: BMC Bioinformatics 2019 20:185

    Content type: Methodology article

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  31. The design of an experiment influences both what a researcher can measure, as well as how much confidence can be placed in the results. As such, it is vitally important that experimental design decisions do no...

    Authors: Daphne Ezer and Joseph Keir

    Citation: BMC Bioinformatics 2019 20:166

    Content type: Methodology article

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  32. RNA-Seq technology is routinely used to characterize the transcriptome, and to detect gene expression differences among cell types, genotypes and conditions. Advances in short-read sequencing instruments such ...

    Authors: Refael Kohen, Jonathan Barlev, Gil Hornung, Gil Stelzer, Ester Feldmesser, Kiril Kogan, Marilyn Safran and Dena Leshkowitz

    Citation: BMC Bioinformatics 2019 20:154

    Content type: Software

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2019 Journal Metrics

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    3.242 - 2-year Impact Factor
    3.213 - 5-year Impact Factor
    1.156 - Source Normalized Impact per Paper (SNIP)
    1.626 - SCImago Journal Rank (SJR)

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