A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling

<p>Abstract</p> <p>Background</p> <p>RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci.</p> <p>Results</p> <p>We found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to <it>t</it><1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions.</p> <p>Conclusions</p> <p>By focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.</p

The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

BACKGROUND: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses. RESULTS: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics. CONCLUSION: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Bootstrapping a culture of sharing to facilitate open educational resources

It seems self evident that life for teachers would be simplified if there existed a large corpus of relevant resources that was available for them to re-use, and for inquisitive students to download. The learning object community has worked for the past decade and more to provide the necessary infrastructure, standards and specifications to facilitate such beneficial activity, but the take-up has been disappointingly small, particularly in University and Higher Education, which is the subject of this research. The problem has been that practitioners have not deposited their teaching resources, or have not made them openly available, in the quantity that would achieve critical mass for uptake. EdShare and the Language Box are two initiatives that have concentrated on the issue of facilitating and improving the practice of sharing, the former in an institutional setting and the latter in a subject community of practice. This paper describes and analyses the motivations for these projects, the design decisions they took in implementing their repositories, the approaches they took to change agency and practice within their communities, and the changes in practice that have so far been observed. The contribution of this paper is an improved understanding of how to encourage educational communities to share

Amplification protocols introduce systematic but reproducible errors into gene expression studies

The desire to perform microarray experiments with small starting amounts of RNA has led to the development of a variety of protocols for preparing and amplifying mRNA. This has consequences not only for the standardization of experimental design, but also for reproducibility and comparability between experiments. Here we investigate the differences between the Affymetrix standard and small sample protocols and address the data analysis issues that arise when comparing samples and experiments that have been processed in different ways. We show that data generated on the same platform using different protocols are not directly comparable. Further, protocols introduce systematic biases that can be largely accounted for by using the correct data analysis techniques. </jats:p

High correspondence between Affymetrix exon and standard expression arrays

Exon arrays aim to provide comprehensive gene expression data at the level of individual exons, similar to that provided on a per-gene basis by existing expression arrays. This report describes the performance of Affymetrix GeneChip® Human Exon 1.0 ST array by using replicated RNA samples from two human cell lines, MCF7 and MCF10A, hybridized both to Exon 1.0 ST and to HG-U133 Plus2 arrays. Cross-comparison between array types requires an appropriate mapping to be found between individual probe sets. Three possible mappings were considered, reflecting different strategies for dealing with probe sets that target different parts of the same transcript. Irrespective of the mapping used, Exon 1.0 ST and HG-U133 Plus2 arrays show a high degree of correspondence. More than 80% of HG-U133 Plus2 probe sets may be mapped to the Exon chip, and fold changes are found well preserved for over 96% of those probe sets detected present. Since HG-U133 Plus2 arrays have already been extensively validated, these results lend a significant degree of confidence to exon arrays

Through the looking glass: publishing in peer reviewed academic journals

This paper considers some of the issues of power embedded in publishing in academic journals. It asks questions about the way in which individual scholars and researchers might be empowered within a hierarchical system in which getting funding and getting published are closely allied. Four concepts borrowed from diverse sources (creative power, the power to disbelieve, power as freedom and decisive preference) act as running stitches through an auto/biographical account of my return to the academy after an absence of several years. Showing how I exercised power as a PhD student I conclude on a polemical but somewhat speculative note as a scholar who has yet to find a home