Guide to data analysis and quality control using cusum techniques

1980 ◽  
1972 ◽  
Vol 18 (3) ◽  
pp. 250-257 ◽  
Author(s):  
J H Riddick ◽  
Roger Flora ◽  
Quentin L Van Meter

Abstract A system of quality-control data analysis by computer is described, in which two-way analysis of variance is used for partitioning sources of laboratory error into day-to-day, within-day, betweenpools and additivity variation. The partition for additivity is described in detail as to its advantages and applications. In addition, control charts based on two-way analysis of variance computations are prepared each month by computer. This computer program is designed to operate with the IBM 1800 or 1130 computers or any computer with a Fortran IV compiler. Examples are presented of use of the control charts and of tables of analysis of variance.


Planta Medica ◽  
2021 ◽  
Author(s):  
Luiz C. Klein-Junior ◽  
Maira R. de Souza ◽  
Johan Viaene ◽  
Tania M. B. Bresolin ◽  
André L. de Gasper ◽  
...  

AbstractHerbal medicines are important options for the treatment of several illnesses. Although their therapeutic applicability has been demonstrated throughout history, several concerns about their safety and efficacy are raised regularly. Quality control of articles of botanical origin, including plant materials, plant extracts, and herbal medicines, remains a challenge. Traditionally, qualitative (e.g., identification and chromatographic profile) and quantitative (e.g., content analyses) markers are applied for this purpose. The compound-oriented approach may stand alone in some cases (e.g., atropine in Atropa belladonna). However, for most plant materials, plant extracts, and herbal medicines, it is not possible to assure quality based only on the content or presence/absence of one (sometimes randomly selected) compound. In this sense, pattern-oriented approaches have been extensively studied, introducing the use of multivariate data analysis on chromatographic/spectroscopic fingerprints. The use of genetic methods for plant material/plant extract authentication has also been proposed. In this study, traditional approaches are reviewed, although the focus is on the applicability of fingerprints for quality control, highlighting the most used approaches, as well as demonstrating their usefulness. The literature review shows that a pattern-oriented approach may be successfully applied to the quality assessment of articles of botanical origin, while also providing directions for a compound-oriented approach and a rational marker selection. These observations indicate that it may be worth considering to include fingerprints and their data analysis in the regulatory framework for herbal medicines concerning quality control since this is the foundation of the holistic view that these complex products demand.


2021 ◽  
Author(s):  
Melanie Christine Föll ◽  
Veronika Volkmann ◽  
Kathrin Enderle-Ammour ◽  
Konrad Wilhelm ◽  
Dan Guo ◽  
...  

Background: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens. This allows for spatial characterization of molecular compositions of different tissue types and tumor subtypes, which bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of an urothelial carcinoma dataset. Methods: Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle invasive urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. Results: Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle invasive tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: Stromal tissue was characterized by collagen type I peptides and tumor tissue by histone and heat shock protein beta-1 peptides. Intermediate filaments such as cytokeratins and vimentin were discriminative between the tumors with different muscle-infiltration status. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. Conclusion: Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.


2018 ◽  
Author(s):  
Leandro Gabriel Roser ◽  
Fernán Agüero ◽  
Daniel Oscar Sánchez

AbstractBackgroundExploration and processing of FASTQ files are the first steps in state-of-the-art data analysis workflows of Next Generation Sequencing (NGS) platforms. The large amount of data generated by these technologies has put a challenge in terms of rapid analysis and visualization of sequencing information. Recent integration of the R data analysis platform with web visual frameworks has stimulated the development of user-friendly, powerful, and dynamic NGS data analysis applications.ResultsThis paper presents FastqCleaner, a Bioconductor visual application for both quality-control (QC) and pre-processing of FASTQ files. The interface shows diagnostic information for the input and output data and allows to select a series of filtering and trimming operations in an interactive framework. FastqCleaner combines the technology of Bioconductor for NGS data analysis with the data visualization advantages of a web environment.ConclusionsFastqCleaner is an user-friendly, offline-capable tool that enables access to advanced Bioconductor infrastructure. The novel concept of a Bioconductor interactive application that can be used without the need for programming skills, makes FastqCleaner a valuable resource for NGS data analysis.


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