80
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Motivation: The NanoString nCounter Platform is a new and promising technology for measuring nucleic acid abundances. It has several advantages over PCR-based techniques, including avoidance of amplification, direct sequence interrogation and digital detection for absolute quantification. These features minimize aspects of experimental error and hold promise for dealing with challenging experimental conditions such as archival formalin-fixed paraffin-embedded samples. However, systematic inter-sample technical artifacts caused by variability in sample preservation, bio-molecular extraction and platform fluctuations must be removed to ensure robust data.

          Results: To facilitate this process and to address these issues for NanoString datasets, we have written a pre-processing package called NanoStringNorm in the R statistical language. Key features include an extensible environment for method comparison and new algorithm development, integrated gene and sample diagnostics, and facilitated downstream statistical analysis. The package is open-source, is available through the CRAN package repository, includes unit-tests to ensure numerical accuracy, and provides visual and numeric diagnostics.

          Availability: http://cran.r-project.org/web/packages/NanoStringNorm

          Contact: paul.boutros@ 123456oicr.on.ca

          Supplementary information: Supplementary data are available at Bioinformatics online.

          Related collections

          Most cited references7

          • Record: found
          • Abstract: found
          • Article: not found

          Direct multiplexed measurement of gene expression with color-coded probe pairs.

          We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Robust global micro-RNA profiling with formalin-fixed paraffin-embedded breast cancer tissues.

            Global micro-RNA (miR) profiling of human malignancies is increasingly performed, but to date, the majority of such analyses have used frozen tissues. However, formalin fixation is the standard and routine histological practice for optimal preservation of cellular morphology. To determine whether miR analysis of formalin-fixed tissues is feasible, quantitative real-time PCR (qRT-PCR) profiling of miR expression in 40 archival formalin-fixed paraffin-embedded (FFPE) breast lumpectomy specimens were performed. Taqman Low Density Arrays (TLDAs) were used to assess the expression level of 365 miRs in 34 invasive ductal carcinomas and in 6 normal comparators derived from reduction mammoplasties. Its technical reproducibility was high, with intra-sample correlations above 0.9 and with 92.8% accuracy in differential expression comparisons, indicating such global profiling studies to be technically and biologically robust. The TLDA data were confirmed using conventional single-well qRT-PCR analysis, showing a strong and statistically significant concordance between these two methods. Paired frozen and FFPE breast cancer samples from the same patients showed a similar level of robust correlation of at least 0.94. Compared with normal breast samples, a panel of miRs was consistently dysregulated in breast cancer, including earlier-reported breast cancer-related miRs, such as upregulated miR-21, miR-155, miR-191, and miR-196a, and downregulated miR-125b and miR-221. Additional novel miR sequences of potential biological relevance were also uncovered. These results show the validity and utility of conducting global miR profiling using FFPE samples, thereby offering enormous opportunities to evaluate archival banks of such materials, linked to clinical databases, to rapidly acquire greater insight into the clinically relevant role for miRs in human malignancies.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Using RNA sample titrations to assess microarray platform performance and normalization techniques.

              We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.
                Bookmark

                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                1 June 2012
                17 April 2012
                17 April 2012
                : 28
                : 11
                : 1546-1548
                Affiliations
                1Informatics and Biocomputing Platform, Ontario Institute for Cancer Research, Toronto, Canada M5G 0A3, 2Ontario Cancer Institute and Campbell Family Institute for Cancer Research, Princess Margaret Hospital, University Health Network and 3Departments of Radiation Oncology and Medical Biophysics, University of Toronto, Toronto, Canada, M5G 2M9
                Author notes
                * To whom correspondence should be addressed.

                Associate Editor: Ivo Hofacker

                Article
                bts188
                10.1093/bioinformatics/bts188
                3356845
                22513995
                f6fe5659-eeba-496e-a0da-0dc8090c88c0
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 September 2011
                : 24 March 2012
                : 11 April 2012
                Page count
                Pages: 3
                Categories
                Applications Note
                Gene Expression

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

                Comments

                Comment on this article