MRC-Holland - MLPA Procedure - Data analysis

	introduction
	experimental set up
	sample treatment
	MLPA reaction
	fragment separation
	raw data evaluation
	peak pattern evaluation
	data analysis
	result interpretation
	troubleshooting

new products
P339-SHANK3 Autism Spectrum Disorder
P010-POLG Mitochondrial maintenance
P366-CHM-RP2-RPGR Retinitis pigmentosa (RP)
P350-CLCN1-KCNJ2 Myotonia congenita, Thomsen’s disease, Becker’s disease, Andersen-Tawil syndrome
P273-PCSK5 Atherosclerotic cardiovascular disease (risk of)

improved products
P044-NF2 Neurofibromatosis type 2 (NF2)
P199-HEXA Tay-sachs disease
P214-COL2A1 Skeletal disorders, Achondrogenesis, Chondrodysplasia, Early onset familial Osteoarthritis, SED congenital, Langer-Saldino achondrogenesis, Kniest dysplasia, Stickler syndrome, Spondyloepimetaphyseal
P280-SLC26A4 Pendred syndrome
P026-Sotos Sotos syndrome
ME011-MMR Mismatch repair genes (MMR)

MLPA^® Data Analysis

Since normalisation of the electrophoresis results is essential for obtaining useful MLPA data, data analysis forms a crucial step of the MLPA procedure. Data analysis can be done when your data has passed the raw data and peak pattern evaluation.

Coffalyser MLPA data analysis software
MRC-Holland recommends using Coffalyser software for the analysis of your MLPA data. Coffalyser is an Excel-based program which runs on a Microsoft Office version 2003+. All data normalization steps are built-in functions of Coffalyser. Furthermore, Coffalyser corrects for signal sloping. Coffalyser can be downloaded freely from our website and is updated regularly. An Excel-independent version will be released mid 2009.

Other methods
Several laboratories kindly provide free Excel sheets for the analysis of several probe mixes. Commercial software to analyze MLPA data is also available. Please note that neither of these correct for signal sloping.

About MLPA data normalisation
This document contains more information about MLPA data normalisation.

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