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In-Depth Comparative Analysis Research Paper

Qualitative comparative analysis (QCA) appears to offer a systematic means for case-oriented analysis. The method not only offers to provide a standardized procedure for qualitative research but also serves, to some, as an instantiation of deterministic methods. Others, however, contest QCA because of its deterministic lineage. Multiple other issues surrounding QCA, such as its response to measurement error and its ability to ascertain asymmetric causality, are also matters of interest. Existing research has demonstrated the use of QCA on real data, but such data do not allow one to establish the method’s efficacy, because the true causes of real social phenomena are always contestable. In response, the authors analyze several simulated data sets for which true causal processes are known. They find that QCA finds the correct causal story only 3 times across 70 different solutions, and even these rare successes, on closer examination, actually reveal additional fundamental problems with the method. Further epistemological analyses of the results find key problems with QCA’s stated epistemology, and results indicate that QCA fails even when its stated epistemological claims are ontologically accurate. Thus, the authors conclude that analysts should reject both QCA and its epistemological justifications in favor of existing effective methods and epistemologies for qualitative research.

Quantitative proteomics using LC-MS has emerged as an essential tool for addressing different biological questions. Various labelling methods have been effectively employed for quantitative proteomics studies. However, these are fraught with several challenges, including reproducibility and the number of samples that can be analysed at a given time. To this end, unlabelled proteomics is a promising field, and the recently developed sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) method aims to address these limitations. In this study, we compared SWATH-MS to isobaric tag for relative and absolute quantitation (iTRAQ), a widely used labelled method for relative quantitation. For this, we used yeast, Saccharomyces cerevisiae, since almost all its proteins are identified. More importantly, the abundance of each protein is well documented. We found that although a similar number of proteins could be quantitated using the two techniques, SWATH had the advantage of quantifying a larger percentage of low abundance proteins (below 60 ppm). Thus, based on our analysis, we believe that these two techniques are complementary and can synergistically improve the number of quantifiable proteins. SWATH's ability to quantify low abundant proteins could be an asset in biomarker discovery studies.

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