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Figure 1 | BMC Bioinformatics

Figure 1

From: MIPHENO: data normalization for high throughput metabolite analysis

Figure 1

Flowchart of MIPHENO. "Input Data" (1) contains data with identifiable parameters for grouping/processing the data. The data pass through a quality control (QC) removal step (2), where groups not meeting the cut offs are identified and removed on an attribute-by-attribute basis. Data are normalized (3) using a scaling factor based on the data distribution. Putative hits are identified (4) using a CDF built from the data or user defined NULL distribution and an empirical p-value is assigned to each observation. Thresholds can be established based on follow-up capacity and prior knowledge (e.g. ability to detect known 'gold standard' mutant samples).

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