ArticleGenome research2010
Gene expression profiling of human breast tissue samples using SAGE-Seq.
Article in Genome research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 41 citations in OpenAlex.
- KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance.Cancer cell · 2018Article
- CRISPRcloud: a secure cloud-based pipeline for CRISPR pooled screen deconvolution.Bioinformatics (Oxford, England) · 2017Article
- Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes.Cancer research · 2016Article
- Article
- Diversity of Gene Expression in Hepatocellular Carcinoma Cells.Genomics, proteomics & bioinformatics · 2015Article
- PAT-seq: a method to study the integration of 3'-UTR dynamics with gene expression in the eukaryotic transcriptome.RNA (New York, N.Y.) · 2015Article
- Article
- Transcriptome analysis of the Bombyx mori fat body after constant high temperature treatment shows differences between the sexes.Molecular biology reports · 2014Article
- Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.Genome research · 2014Article
- Ductal carcinoma in situ of the breast: morphological and molecular features implicated in progression.Bioscience reports · 2014Review
- Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics.Cell stem cell · 2013Article
- Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions.Genome research · 2013Article
- 24 hours in the life of HIV-1 in a T cell line.PLoS pathogens · 2013Article
- Deconvoluting complex tissues for expression quantitative trait locus-based analyses.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2013Article
- Optimal scaling of digital transcriptomes.PloS one · 2013Article
- QChIPat: a quantitative method to identify distinct binding patterns for two biological ChIP-seq samples in different experimental conditions.BMC genomics · 2013Article
- RNA sequencing of cancer reveals novel splicing alterations.Scientific reports · 2013Article
- Minireview: applications of next-generation sequencing on studies of nuclear receptor regulation and function.Molecular endocrinology (Baltimore, Md.) · 2012Review
- Article
- Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.Nucleic acids research · 2012Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.