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Genetics and evolution science fair projects, revised and expanded using the scientific method
\"Explains how to use the scientific method to conduct several science experiments about genetics and evolution. Includes ideas for science fair projects\"--Provided by publisher.
BOOK
Investigating the replicability of preclinical cancer biology
Replicability is an important feature of scientific research, but aspects of contemporary research culture, such as an emphasis on novelty, can make replicability seem less important than it should be. The Reproducibility Project: Cancer Biology was set up to provide evidence about the replicability of preclinical research in cancer biology by repeating selected experiments from high-impact papers. A total of 50 experiments from 23 papers were repeated, generating data about the replicability of a total of 158 effects. Most of the original effects were positive effects (136), with the rest being null effects (22). A majority of the original effect sizes were reported as numerical values (117), with the rest being reported as representative images (41). We employed seven methods to assess replicability, and some of these methods were not suitable for all the effects in our sample. One method compared effect sizes: for positive effects, the median effect size in the replications was 85% smaller than the median effect size in the original experiments, and 92% of replication effect sizes were smaller than the original. The other methods were binary – the replication was either a success or a failure – and five of these methods could be used to assess both positive and null effects when effect sizes were reported as numerical values. For positive effects, 40% of replications (39/97) succeeded according to three or more of these five methods, and for null effects 80% of replications (12/15) were successful on this basis; combining positive and null effects, the success rate was 46% (51/112). A successful replication does not definitively confirm an original finding or its theoretical interpretation. Equally, a failure to replicate does not disconfirm a finding, but it does suggest that additional investigation is needed to establish its reliability.
Journal Article
Step-by-step science experiments in biology
Detailed instructions lead the user into brief experiments involving biology.
Book
Challenges for assessing replicability in preclinical cancer biology
We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology. The initial aim of the project was to repeat 193 experiments from 53 high-impact papers, using an approach in which the experimental protocols and plans for data analysis had to be peer reviewed and accepted for publication before experimental work could begin. However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments. Third, once experimental work started, 67% of the peer-reviewed protocols required modifications to complete the research and just 41% of those modifications could be implemented. Cumulatively, these three factors limited the number of experiments that could be repeated. This experience draws attention to a basic and fundamental concern about replication – it is hard to assess whether reported findings are credible.
Journal Article
Cell and microbe science fair projects : revised and expanded using the scientific method
A collection of science experiments about cells and microbes with emphasis on using the scientific method.
Book
Making sense of replications
The first results from the Reproducibility Project: Cancer Biology suggest that there is scope for improving reproducibility in pre-clinical cancer research.DOI:http://dx.doi.org/10.7554/eLife.23383.001
Journal Article
An open investigation of the reproducibility of cancer biology research
It is widely believed that research that builds upon previously published findings has reproduced the original work. However, it is rare for researchers to perform or publish direct replications of existing results. The Reproducibility Project: Cancer Biology is an open investigation of reproducibility in preclinical cancer biology research. We have identified 50 high impact cancer biology articles published in the period 2010-2012, and plan to replicate a subset of experimental results from each article. A Registered Report detailing the proposed experimental designs and protocols for each subset of experiments will be peer reviewed and published prior to data collection. The results of these experiments will then be published in a Replication Study. The resulting open methodology and dataset will provide evidence about the reproducibility of high-impact results, and an opportunity to identify predictors of reproducibility.
Journal Article
What have we learned?
As the final outputs of the Reproducibility Project: Cancer Biology are published, it is clear that preclinical research in cancer biology is not as reproducible as it should be.As the final outputs of the Reproducibility Project: Cancer Biology are published, it is clear that preclinical research in cancer biology is not as reproducible as it should be.
Journal Article
Replication Study: Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma
As part of the Reproducibility Project: Cancer Biology, we published a Registered Report (Repass et al., 2016), that described how we intended to replicate an experiment from the paper ‘Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma’ (Castellarin et al., 2012). Here we report the results. When measuring Fusobacterium nucleatum DNA by qPCR in colorectal carcinoma (CRC), adjacent normal tissue, and separate matched control tissue, we did not detect a signal for F. nucleatum in most samples: 25% of CRCs, 15% of adjacent normal, and 0% of matched control tissue were positive based on quantitative PCR (qPCR) and confirmed by sequencing of the qPCR products. When only samples with detectable F. nucleatum in CRC and adjacent normal tissue were compared, the difference was not statistically significant, while the original study reported a statistically significant increase in F. nucleatum expression in CRC compared to adjacent normal tissue (Figure 2; Castellarin et al., 2012). Finally, we report a meta-analysis of the result, which suggests F. nucleatum expression is increased in CRC, but is confounded by the inability to detect F. nucleatum in most samples. The difference in F. nucleatum expression between CRC and adjacent normal tissues was thus smaller than the original study, and not detected in most samples.
Journal Article
Is preclinical research in cancer biology reproducible enough?
The Reproducibility Project: Cancer Biology (RPCB) was established to provide evidence about reproducibility in basic and preclinical cancer research, and to identify the factors that influence reproducibility more generally. In this commentary we address some of the scientific, ethical and policy implications of the project. We liken the basic and preclinical cancer research enterprise to a vast 'diagnostic machine' that is used to determine which clinical hypotheses should be advanced for further development, including clinical trials. The results of the RPCB suggest that this diagnostic machine currently recommends advancing many findings that are not reproducible. While concerning, we believe that more work needs to be done to evaluate the performance of the diagnostic machine. Specifically, we believe three questions remain unanswered: how often does the diagnostic machine correctly recommend against advancing real effects to clinical testing?; what are the relative costs to society of false positive and false negatives?; and how well do scientists and others interpret the outputs of the machine?
Journal Article