Computational protocol: A Molecular Signature of Myalgia in Myotonic Dystrophy 2

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Protocol publication

[…] All statistical calculations were performed using R software. The QST parameters – CDT, WDT, PPT, WUR, MPS, MDT, and MPT – are usually normally distributed in log-space and thus were log-transformed. The QST-profiles of DM2 patients were compared to controls using repeated measure two factorial (for group and tested site) ANOVA. All QST measures from each patient were then standardized by z-transformation with respect to the age- and sex-matched healthy subject group.Z-score=MeanindividualDM2−Meanhealthy subjects/SDhealthy subjectswhere mean individual DM2 is the value of the QST parameter in a DM2 patient, and meanhealthy subjects and SDhealthy subjects are mean and standard deviation of the corresponding QST parameter in the healthy control group. Z-scores signs were adjusted so that a z-score > 0 indicated means gain of sensory function (lower threshold), and z-score < 0 means loss of function (increase in threshold). The advantage of graphical representation of QST profiles as z-transformed data was to directly compare between sensory modalities of different units and ranges between groups and tested sites.Gene expression data was analysed with CLC Genomic Workbench v7.0 (Qiagen, Germany) and Qlucore Omics Explorer v3.1 (Qlucore, Denmark). Samples obtained from patients without muscle pain were considered as a reference group. Preprocessed raw sequences were imported and trimmed in CLC Genomics Workbench and all trimmed reads were aligned to the human reference genome (GRCh37) and mapped back to the human transcriptome (v.19). Mapped read counts were normalized using Trimmed mean of M-values (TMM) method implemented in Edge-R package. Normalized read counts were used for analysis of differential gene expression at Qlucore Omics Explorer. P values were calculated by two group comparison T-test. Genes with P-value < 0.05 and fold change >±1.8 were considered to be differentially expressed and were presented as a heatmap with hierarchical clustering of the samples. Differentially expressed genes from RNAseq data were additionally confirmed with qPCR using ∆∆Ct method with the average of Ct values for GAPDH and cyclophilin A used as a reference. Ct values were calculated by MxPro qPCR software v4.1 (Agilent Technologies, USA). Gene functions were analysed using Quick GO gene ontology database (http://www.ebi.ac.uk/QuickGO/). […]

Pipeline specifications

Software tools CLC Genomics Workbench, QuickGO
Application RNA-seq analysis
Organisms Homo sapiens
Diseases Myotonic Dystrophy, Fatigue Syndrome, Chronic, Genetic Diseases, Inborn