Genomics & Proteomics |
Next Generation Sequencing |
Statistical Data Analysis
Statistical data analysis for bioinformatics is the study of biological data sets obtained by biological technologies by means of proper statistical methods.
Once you have collected quantitative data, you have to carry out some statistical analysis to make sense of, and draw some inferences from, them. There is a wide range of possible method that we can use to help you.
We strongly suggest users to contact us before performing experiments in order to define the best strategy among the different solutions.
Experimental design
- Sample size
- Variation
- Measurement error
- Power analysis
Hypothesis testing
Bayesian and frequentist tests, e.g. chi-squared, Student t, ANOVA, Fisher, etc.
Differential expression analysis
Data normalization and batch effect correction.
Analysis of differential gene expression in microarray and RNA-seq data.
Vulcano Plot: reference
Clustering analysis
Clustering of gene expression data
Time series data analysis
Analysis of Time Series expression data from Microarray, RNA-seq, Real Time Q-PCR and other experiments.
Times Series: reference
Survival analysis
Survival analysis is a branch of statistics for analyzing the expected duration of time until one or more events happen, such as death in biological organisms and failure in mechanical systems.
