![]() When replicate blood specimens from the same patient are measured on a CyTOF machine in different batches (e.g. Typically, the systematic effect of varying instrument conditions on the measurements depends on many unknown factors, whose impact on the difference between the observed and underlying true signal cannot be modeled.įor example, CyTOF, a mass cytometry technique for measuring multiple protein levels in many cells of a biological specimen, is known to incur batch effects. Batch effects introduce systematic error, which may cause statistical analysis to produce spurious results and/or obfuscate the signal of interest. The term batch effects, often used in the biological community, describes a situation where subsets (batches) of the measurements significantly differ in distribution, due to irrelevant instrument-related factors ( Leek et al., 2010). For example, two distributions of multidimensional molecular data generated from two identical blood drops of the same person (technical replicates) in two experimental batches, may deviate from each other due to variation in conditions between batches. ![]() Biological data are affected by the conditions of the measuring instruments. ![]()
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