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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. Cap analysis of gene expression (CAGE) is a sequencing based technology to capture the 5’ ends of RNAs in a biological sample. After mapping, a CAGE peak on the genome indicates the position of an active trans...

    Authors: Akira Hasegawa, Carsten Daub, Piero Carninci, Yoshihide Hayashizaki and Timo Lassmann

    Citation: BMC Bioinformatics 2014 15:144

    Content type: Software

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  2. DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history o...

    Authors: Minta Thomas, Kris De Brabanter and Bart De Moor

    Citation: BMC Bioinformatics 2014 15:137

    Content type: Methodology article

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  3. Computational discovery of microRNAs (miRNA) is based on pre-determined sets of features from miRNA precursors (pre-miRNA). Some feature sets are composed of sequence-structure patterns commonly found in pre-m...

    Authors: Ivani de ON Lopes, Alexander Schliep and André CP de LF de Carvalho

    Citation: BMC Bioinformatics 2014 15:124

    Content type: Research article

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  4. Complex designs are common in (observational) clinical studies. Sequencing data for such studies are produced more and more often, implying challenges for the analysis, such as excess of zeros, presence of ran...

    Authors: Mark A van de Wiel, Maarten Neerincx, Tineke E Buffart, Daoud Sie and Henk MW Verheul

    Citation: BMC Bioinformatics 2014 15:116

    Content type: Software

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  5. It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogen...

    Authors: Ståle Nygård, Trond Reitan, Trevor Clancy, Vegard Nygaard, Johannes Bjørnstad, Biljana Skrbic, Theis Tønnessen, Geir Christensen and Eivind Hovig

    Citation: BMC Bioinformatics 2014 15:115

    Content type: Methodology article

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  6. The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most ...

    Authors: Juuso A Parkkinen and Samuel Kaski

    Citation: BMC Bioinformatics 2014 15:113

    Content type: Methodology article

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  7. High-throughput sequencing is now regularly used for studies of the transcriptome (RNA-seq), particularly for comparisons among experimental conditions. For the time being, a limited number of biological repli...

    Authors: Andrea Rau, Guillemette Marot and Florence Jaffrézic

    Citation: BMC Bioinformatics 2014 15:91

    Content type: Methodology article

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  8. Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) ...

    Authors: Fabian Amman, Michael T Wolfinger, Ronny Lorenz, Ivo L Hofacker, Peter F Stadler and Sven Findeiß

    Citation: BMC Bioinformatics 2014 15:89

    Content type: Software

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  9. The circadian clock is a critical regulator of biological functions controlling behavioral, physiological and biochemical processes. Because the liver is the primary regulator of metabolites within the mammali...

    Authors: Tung T Nguyen, John SA Mattick, Qian Yang, Mehmet A Orman, Marianthi G Ierapetritou, Francois Berthiaume and Ioannis P Androulakis

    Citation: BMC Bioinformatics 2014 15:83

    Content type: Research article

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  10. RNA-seq data is currently underutilized, in part because it is difficult to predict the functional impact of alternate transcription events. Recent software improvements in full-length transcript deconvolution...

    Authors: Kristoffer Vitting-Seerup, Bo Torben Porse, Albin Sandelin and Johannes Waage

    Citation: BMC Bioinformatics 2014 15:81

    Content type: Software

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  11. Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Anal...

    Authors: Neil R Clark, Kevin S Hu, Axel S Feldmann, Yan Kou, Edward Y Chen, Qiaonan Duan and Avi Ma’ayan

    Citation: BMC Bioinformatics 2014 15:79

    Content type: Research article

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  12. MicroRNAs (miRNAs) are short (19-23 nucleotides) non-coding RNAs that bind to sites in the 3’untranslated regions (3’UTR) of a targeted messenger RNA (mRNA). Binding leads to degradation of the transcript or b...

    Authors: Mehmet Deveci, Ümit V Çatalyürek and Amanda Ewart Toland

    Citation: BMC Bioinformatics 2014 15:73

    Content type: Software

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  13. Molecular data, e.g. arising from microarray technology, is often used for predicting survival probabilities of patients. For multivariate risk prediction models on such high-dimensional data, there are establ...

    Authors: Murat Sariyar, Isabell Hoffmann and Harald Binder

    Citation: BMC Bioinformatics 2014 15:58

    Content type: Research article

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  14. In the application of microarray data, how to select a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers is an important issue. Many researchers use var...

    Authors: Kun-Huang Chen, Kung-Jeng Wang, Min-Lung Tsai, Kung-Min Wang, Angelia Melani Adrian, Wei-Chung Cheng, Tzu-Sen Yang, Nai-Chia Teng, Kuo-Pin Tan and Ku-Shang Chang

    Citation: BMC Bioinformatics 2014 15:49

    Content type: Methodology article

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  15. A challenge in gene expression studies is the reliable identification of differentially expressed genes. In many high-throughput studies, genes are accepted as differentially expressed only if they satisfy sim...

    Authors: Evelien Vaes, Mona Khan and Peter Mombaerts

    Citation: BMC Bioinformatics 2014 15:39

    Content type: Methodology article

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  16. Cancer subtype information is critically important for understanding tumor heterogeneity. Existing methods to identify cancer subtypes have primarily focused on utilizing generic clustering algorithms (such as...

    Authors: Yiyi Liu, Quanquan Gu, Jack P Hou, Jiawei Han and Jian Ma

    Citation: BMC Bioinformatics 2014 15:37

    Content type: Methodology article

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  17. Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have ...

    Authors: Rimpi Khurana, Vinod Kumar Verma, Abdul Rawoof, Shrish Tiwari, Rekha A Nair, Ganesh Mahidhara, Mohammed M Idris, Alan R Clarke and Lekha Dinesh Kumar

    Citation: BMC Bioinformatics 2014 15:15

    Content type: Database

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  18. The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying ...

    Authors: Jianlong Qi, Hassan Foroughi Asl, Johan Björkegren and Tom Michoel

    Citation: BMC Bioinformatics 2014 15:11

    Content type: Software

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  19. Gene selection is an important part of microarray data analysis because it provides information that can lead to a better mechanistic understanding of an investigated phenomenon. At the same time, gene selecti...

    Authors: Miron Bartosz Kursa

    Citation: BMC Bioinformatics 2014 15:8

    Content type: Research article

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  20. RNA-seq is now widely used to quantitatively assess gene expression, expression differences and isoform switching, and promises to deliver results for the entire transcriptome. However, whether the transcripti...

    Authors: Hubert Rehrauer, Lennart Opitz, Ge Tan, Lina Sieverling and Ralph Schlapbach

    Citation: BMC Bioinformatics 2013 14:370

    Content type: Research article

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  21. As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have b...

    Authors: Lun-Ching Chang, Hui-Min Lin, Etienne Sibille and George C Tseng

    Citation: BMC Bioinformatics 2013 14:368

    Content type: Research article

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  22. Significance analysis plays a major role in identifying and ranking genes, transcription factor binding sites, DNA methylation regions, and other high-throughput features associated with illness. We propose a ...

    Authors: Andrew E Jaffe, John D Storey, Hongkai Ji and Jeffrey T Leek

    Citation: BMC Bioinformatics 2013 14:360

    Content type: Methodology article

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  23. The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution a...

    Authors: David Sturgill, John H Malone, Xia Sun, Harold E Smith, Leonard Rabinow, Marie-Laure Samson and Brian Oliver

    Citation: BMC Bioinformatics 2013 14:320

    Content type: Methodology article

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  24. The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of...

    Authors: Ivan Molineris, Ugo Ala, Paolo Provero and Ferdinando Di Cunto

    Citation: BMC Bioinformatics 2013 14:288

    Content type: Research article

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  25. Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the und...

    Authors: Juliane Charlotte Thøgersen, Morten Mørup, Søren Damkiær, Søren Molin and Lars Jelsbak

    Citation: BMC Bioinformatics 2013 14:279

    Content type: Research article

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  26. Chromatin immunoprecipitation coupled with hybridization to a tiling array (ChIP-chip) is a cost-effective and routinely used method to identify protein-DNA interactions or chromatin/histone modifications. The...

    Authors: Caroline Bérard, Michael Seifert, Tristan Mary-Huard and Marie-Laure Martin-Magniette

    Citation: BMC Bioinformatics 2013 14:271

    Content type: Software

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  27. New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resultin...

    Authors: Terrence F Meehan, Nicole A Vasilevsky, Christopher J Mungall, David S Dougall, Melissa A Haendel, Judith A Blake and Alexander D Diehl

    Citation: BMC Bioinformatics 2013 14:263

    Content type: Methodology article

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  28. Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes...

    Authors: Jonathan A Gelfond, Joseph G Ibrahim, Mayetri Gupta, Ming-Hui Chen and Jannine D Cody

    Citation: BMC Bioinformatics 2013 14:258

    Content type: Methodology article

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  29. High-throughput RNA sequencing (RNA-seq) offers unprecedented power to capture the real dynamics of gene expression. Experimental designs with extensive biological replication present a unique opportunity to e...

    Authors: Mikel Esnaola, Pedro Puig, David Gonzalez, Robert Castelo and Juan R Gonzalez

    Citation: BMC Bioinformatics 2013 14:254

    Content type: Methodology article

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  30. Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks suc...

    Authors: James Hensman, Neil D Lawrence and Magnus Rattray

    Citation: BMC Bioinformatics 2013 14:252

    Content type: Research article

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  31. In addition to probe sequence characteristics, noise in hybridization array data is thought to be influenced by competitive hybridization between probes tiled at high densities. Empirical evaluation of competi...

    Authors: Cali E Willet, Laura Bunbury-Cruickshank, Diane van Rooy, Georgina Child, Mohammad R Shariflou, Peter C Thomson and Claire M Wade

    Citation: BMC Bioinformatics 2013 14:231

    Content type: Research article

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  32. Frequent pattern mining analysis applied on microarray dataset appears to be a promising strategy for identifying relationships between gene expression levels. Unfortunately, too many itemsets (co-expressed ge...

    Authors: Yu-Cheng Liu, Chun-Pei Cheng and Vincent S Tseng

    Citation: BMC Bioinformatics 2013 14:230

    Content type: Methodology article

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