Gene expression microarray Disadvantages: difficult to process cross-platform data
RNA¬-Seq Advantages: big data, accurate, cost-effective.
①adapter trimming，demiltiplexing
The sequencing libraries usually contain large amount of adapter sequencing which can not be aligned to genome. Therefore, it is required to process the raw data before large-scale sequence alignment, such as adapter trimming and demultiplexing.
②mapping to genome
Since the origin of species and sample types RNA sample, we need to select the appropriate genome sequence alignment; the most common include Ensembl human genome assembly and UCSF Homo sapiens GRCh38 genome. We have equipped with big Server system, which can maximize service speed for sequencing data analysis.
③Raw data normalization
The raw data is processed through a specific statistical analysis to eliminate background noise, filter dirty data, remove experimental error, so that the different sequencing data are comparable.
④Differential gene expression analysis
Differentially expressed genes are caused by multiple factors, and it is associated with many diseases. Therefore, it issignificantly important to study differentially expressed genes using bioinformatics and biostatistics to uncover the regulatory mechanisms for diseases.
• High converge
• Maintain splicing information
Sequencing 3~14 day
Data analysis：5～30 day