Project description:The article by Nygaard and others (2016) proposes that applying batch correction approaches to microarray data from studies with unbalanced designs may inadvertently exaggerate the differences observed. In seeking to illustrate their point, Nygaard and others (2016) utilized a dataset (GSE61901) from a study we published (Towfic and others, 2014) and showed that one analysis pipeline utilizing the traditional approach to batch correction (ComBat) yielded over 1000 differentially expressed probesets, while an alternative approach proposed by Nygaard and others (2016). (utilizing batch as a fixed effect and averaging technical replicates) recovered 11 differentially expressed probesets.
Project description:In Response To: Walker RH. Reply to: Tardive dyskinesia-like syndrome due to drugs that do not block dopamine receptors: rare or non-existent: literature review. Tremor Other Hyperkinet Mov. 2019; 9. doi: 10.7916/3rez-p096 Original Article: D'Abreu A, Friedman JH. Tardive dyskinesia-like syndrome due to drugs that do not block dopamine receptors: rare or non-existent: literature review. Tremor Other Hyperkinet Mov. 2018; 8. doi: 10.7916/D8FF58Z9.
Project description:In October 2015 we published the paper 'Measurement of HbA1c in multicentre diabetes trials - should blood samples be tested locally or sent to a central laboratory: an agreement analysis'. Chatterjee and Pradhan have submitted a letter to the editor asking critical questions regarding the methods we used. We offer this letter in response.Trial registrationEudract No. 2010-023792-25. Registered on 4 November 2010. ISRCTN No. ISRCTN29255275 . Registered on 12 November 2010.
Project description:Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of early deaths. The data presented in this article reviews the medical images of breast cancer using ultrasound scan. Breast Ultrasound Dataset is categorized into three classes: normal, benign, and malignant images. Breast ultrasound images can produce great results in classification, detection, and segmentation of breast cancer when combined with machine learning.