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For GBM and OV, we used Agilent microarray data instead since it covers more patients presented in the SFEs binary dataset.
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To look for the ligand that might be important for TNBC tumorigenesis, we performed large scale public microarray data analysis instead of using our limited samples to achieve meaningful significance.
Further, using microarray data from five individual samples instead of the two pooled samples gave similar results (Pearson correlation, r = 0.34, p = 1.1e-9 and r = 0.42, p = 1.5e-14 for microarray and RNA-Seq, respectively; N = 306).
Chen and Zhang (2012) analyzed RNAseq data instead of microarrays under the premise that RNAseq is the preferred method of expression quantification that is not prone to probe biases that are inherent in expression array data and has a wider dynamic range of detection of low-expressed genes (Wang et al. 2009; Xiong et al. 2010; Brawand et al. 2011).
The use of SAGE data instead of available microarray data is mainly because of the much higher reproducibility of SAGE experiments than microarray experiments [27].
Quantitative PCR is a more sensitive method of for gene expression analysis, thus, the qPCR data instead of the microarray data were used for IPA analysis in all cases as we have done in previous work [ 19].
Instead, we analyzed the microarray data for G. metallireducens growing with benzoate versus acetate [ 21].
Instead, we used the microarray data for the identification of interconnected pathways within specific and extremely well characterized lesions.
This is supported by the fact that this enrichment is higher when bAS -collecting multiple sources of functional evidence- is considered instead of mAS (only microarray data).
In our future studies, we will explore more into meta-analysis of microarray data by applying different statistics like meta correlation instead of chi- square statistics.
For convenience, we use the term "gene" instead of "gene feature" in the microarray data descriptions.
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