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Data Analysis & Experimental Design
Maciejewski H. Gene set analysis methods: statistical models and methodological differences. Briefings in Bioinformatics. 2013; [Epub ahead of print]

Pabinger S, et al. A survey of tools for variant analysis of next-generation genome sequencing data. Briefings in Bioinformatics. 2013; [Epub ahead of print]

Kuhn RM, et al. The UCSC genome browser and associated tools. Briefings in Bioinformatics. 2013; 14(2):144-161

Thorvaldsdottir H, et al. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Briefings in Bioinformatics. 2013; 14(2):178-192

Sirbu A, et al. RNA-Seq vs Dual- and Single-Channel Microarray Data: Sensitivity Analysis for Differential Expression and Clustering. PLoS ONE. 2012; 7(12):e50986

Fonseca NA, et al. Tools for mapping high-throughput sequencing data. Bioinformatics. 2012 Dec 15; 28(24):3169-77

Loven J, et al. Revisiting Global Gene Expression Analysis. Cell. 2012 Oct 26; 151(3):476-482

Torri F, et al. Next Generation Sequence Analysis and Computational Genomics Using Graphical Pipeline Workflows. Genes. 2012 Aug; 3(3):545-575

Jia J et al. Consensus Rules in Variant Detection from Next-Generation Sequencing Data. PLoS One. 2012 Jun 8; 7(6):e38470

Lam HY, et al. Detecting and annotating genetic variations using the HugeSeq pipeline. Nature Biotechnology. 2012 Mar 7; 30:226-229

Chatterjee A, et al. Comparison of alignment software for genome-wide bisulphite sequence data. Nucleic Acids Research. 2012 Feb 16; 40(10):e79

Grant JR, et al. In-depth annotation of SNPs arising from resequencing projects using NGS-SNP. Bioinformatics. 2011 Aug 15; 27(16):2300-2301

The ENCODE Project Consortium. A User's Guide to the Encyclopedia of DNA Elements (ENCODE). PLoS Biology. 2011 Apr 19; 9(4):e1001046

Hawkins RD, et al. Next-generation genomics: an integrative approach. Nature Reviews Genetics. 2010 Jul; 11(7):476-486

Li H and Homer N. A survey of sequence alignment algorithms for next-generation sequencing. Briefings in Bioinfomatics. 2010 May; 11(5):473-483

Hu P, Beyene J, Greenwood CMT. Tests for differential gene expression using weights in oligonucleotide microarray experiments. BMC Genomics. 2006; 7(33)

Deep Sequencing
Robinson DR, et al. Identification of recurrent NAB2-STAT6 gene fusions in solitary fibrous tumor by integrative sequencing. Nature Genetics. 2013 Feb; 45:180-185

Kinde I, et al. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Science Translational Medicine. 2013 Jan; 5(167):167ra4

Ramaswami G, et al. Identifying RNA editing sites using RNA sequencing data alone. Nature Methods. 2013 Feb; 10:128-132

Schmitt MW, et al. Detection of ultra-rare mutations by next-generation sequencing. Proceedings of the National Academy of Sciences USA. 2012 Sep; 109(36):14508-14513

The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012 Sep; 489:57-74

Zhang X, et al. Integrative functional genomics identifies an enhancer looping to the SOX9 gene disrupted by the 17q24.3 prostate cancer risk locus. Genome Research. 2012 Aug; 22(8):1437-1446

Shah SP, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature. 2012 Apr; 486:395-399

You JS, et al. OCT4 establishes and maintains nucleosome-depleted regions that provide additional layers of epigenetic regulation of its target genes. Proceedings of the National Academy of Sciences USA. 2011 Aug; 108(35):14497-14502

Tang F, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nature Methods. 2009 April 6, 6:377-382

Guyer M & Felsenfeld A. Future of Genome Sequencing: A white paper for the National Human Genome Research Institute. Posted January 28, 2009.

Chellappan P & Jin H. Discovery of Plant MicroRNAs and Short-Interfering RNAs by Deep Parallel Sequencing. Methods Molecular Biology. 2009, 495:1-12

Pan Q et al. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nature Genetics. 2008, 40:1413-1415

Park PJ. Epigenetics meets next-generation sequencing. Epigenetics 2008, 3(6):318-321

Ji H et al. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nature Biotechnology. 2008, 26(11):1293

Asmann YW et al. Transcriptome Profiling Using Next-Generation Sequencing. Gastroenterology. 2008, 135(5):1466.

For a more extensive list of publications please see the Luminex website. Selected publications follow:

John-Baptiste A, et al. Comparison of 3 kidney injury multiplex panels in rats. International Journal of Toxicology. 2012; 31(6):529-36

Clarke MA, et al. Human Papillomavirus DNA Methylation as a Potential Biomarker for Cervical Cancer. Cancer Epidemiology Biomarkers & Prevention. 2012; 21(12):2125-37

Niu, X, et al. Altered cytokine profiles in patients with Chuvash polycythemia. Am J Hematol. 2008, 84(2):74

Lee, KS, et al. Bioplex analysis of plasma cytokines in Alzheimer's disease and mild cognitive impairment. Immunology Letters. 2008; 121(2):105

Siawaya, JFD, et al. An Evaluation of Commercial Fluorescent Bead-Based Luminex Cytokine Assays. PLoS ONE. 2008; 3(7):e2535

For a more extensive list of publications please see the NanoString website. Selected publications follow:

Viks-Gat I, et al. Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nature Biotechnology. 2013 Mar 17; [Epub ahead of print]

Barde I, et al. A KRAB/KAP1-miRNA Cascade Regulates Erythropoiesis Through Stage-Specific Control of Mitophagy. Science. 2013 Mar 14; [Epub ahead of print]

Cascione L, et al. Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer. PLoS ONE. 2013 Feb 6; 8(2):e55910

Klattenhoff CA, et al. Braveheart, a long noncoding RNA required for cardiovascular lineage commitment. Cell. 2013 Jan 31; 152(3):570-583

Hassan T, et al. Isolation and identification of cell-specific microRNAs targeting a messenger RNA using biotinylated anti-sense oligonucleotide capture affinity technique. Nucleic Acids Research. 2013 Jan 15; [Epub ahead of print]

Golubeva Y, et al. Laser capture microdissection for protein and NanoString RNA analysis. Methods in Molecular Biology. 2013; 931:213-257

Paull D, et al. Nuclear genome transfer in human oocytes eliminates mitochondrial DNA variants. Nature. 2013 Jan31; 493:632-637

Vanharanta S, et al. Epigenetic expansion of VHL-HIF signal output drives multiorgan metastasis in renal cancer. Nature Medicine. 2013; 19:50-56

Loven J, et al. Revisiting Global Gene Expression Analysis. Cell. 2012 Oct 26; 151:476-482

Lin CY, et al. Transcriptional Amplification in Tumor Cells with Elevated c-Myc. Cell. 2012 Sep; 151(1):56-67

Quek S-I, et al. A Multiplex Assay to Measure RNA Transcripts of Prostate Cancer in Urine. PLoS ONE. 2012 Sep 20; 7(9):e45656

Fortina P & Surrey S. Digital mRNA profiling. Nature Biotechnology. 2008; 26(3):293

Payton JE et al. High throughput digital quantification of mRNA abundance in primary human acute myeloid leukemia samples. J Clin Invest. 2009; Epub May 18, 2009

Malkov VA et al. Multiplexed measurements of gene signatures in different analytes using the Nanostring nCounterâ„¢ Assay System. BMC Research Notes. 2009; 2:80

Single-Cell Analysis
Moignard V, et al. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. Nature Cell Biology. 2013; 15:363-372

Welty CJ, et al. Single cell transcriptomic analysis of prostate cancer cells. BMC Molecular Biology. 2013; 14:6

Zrazhevskiy P and Gao X. Quantum dot imaging platform for single-cell molecular profiling. Nature Communications. 2013 Mar 19; 4:1619

Wu M, et al. Single cell microRNA analysis using microfluidic flow cytometry. PLos ONE. 2013; 8(1):e55044

Zhang C, et al. A single cell level based method for copy number variation analysis by low coverage massively parallel sequencing. PLoS ONE. 2013; 8(1):e54236

Chen C-L, et al. Single-cell analysis of circulating tumor cells identifies cumulative expression patterns of EMT-related genes in metastatic prostate cancer. Prostate. 2012 Dec 31; [Epub ahead of print]

Mannello F, et al. Deciphering the single-cell omic: innovative application for translational medicine. Expert Review of Proteomics. 2012 Dec; 9(6):635-648

Owens B. Genomics: The single life. Nature. 2012 Nov 1; 491:27-29

Schubert C. Single-cell analysis: The deepest differences. Nature. 2011 Dec 1; 480:133-137

Stahlberg A and Bengtsson M. Single-cell gene expression profiling using reverse transcription quantitative real-time PCR. Methods. 2010 Apr; 50(4):282-288

Cheong R, et al. Models at the single cell level. Wiley interdisciplinary reviews Systems Biology and Medicine. 2010; 2(1):34-48

Pushkarev D et al. Single-molecule sequencing of an individual human genome. Nature Biotechnology. 2009; 27:847-850

Kortman H, et al. Towards real time analysis of protein secretion from single cells. Lab on a chip. 2009; 9(21);3047-3049

Roach KL and King KR. High throughput single cell bioinformatics. Biotechnology Progress. 2009; 25(6):1772-1779

Nygaard V, Hovig E. Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling. Nucleic Acids Research, 2006, 34(3);996

Rachman H, et al.. Reliable amplification method for bacterial RNA. Journal of Biotechnology. 2006; 126:61

Schindler H, et al.. cRNA target preparation for microarrays: Comparison of gene expression profiles generated with different amplification procedures. Analytical Biochemistry. 2005; 344(1):92

Subkhankulova T and Livesey FJ. Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level. Genome Biology. 2006; 7(3):R18