Table 1.

Factors that impact preanalytical and analytical bias.

Preanalytical bias
Patients information	Age, gender, ethnicity
	Disease subtype and/or severity
	Medical background
	Health background
	Smoking status, alcohol intake, diet, other risk factors
	Drug treatments
	Patient position (seated/standing/lying), daily moment of collection
	Type of control (healthy or disease)
	Location of sample collection (single or multisite)
	Study inclusion and exclusion criteria
Sample characteristics	Number of individuals
	Type (blood, serum, plasma, urine, cerebrospinal fluid, cell lysate, etc.)
	Source (banked or prospectively collected)
Sample-handling procedures	Collection protocols (initial processing, procedure, timing, type of anticoagulant, type of tubes, number of sites, etc.)
	Storage procedures (time, aliquoting, storage materials, temperature, freeze-thaw cycles, etc.)
Analytical bias
Sample-Processing procedures	Fractionation and depletion methods
	Processing steps (denaturation, buffer components, delipidation, etc.)
	Liquid handling methods (automated or manual, technique, equipment, etc.)
Experimental protocols	Array types
	Sample pH and dilution factor
	Quantity of sample loading and position on arrays
	Sample binding, washing and drying procedures
	Matrix addition (type and method)
	Instruments settings
	Number of instruments, locations
	Environmental factors (temperature, humidity percentage)
Data analysis methods	Spectrum processing (baseline subtraction, normalization, alignment, noise reduction, etc.)
	Peak labelling
	Feature selection, statistical analysis
	Classification approaches