군 유전체 해독 생명정보 분석

1. Standard bioinformatics analysis

1. Remove the low-quality reads

2. Remove the adapters

3. Statistics for host contamination rate (If host genome sequence is known)

4. Assembly

4.1 Statistics for assembly result

4.2 Statistics of Contigs' length distribution

5. Complexity Analysis of sample

5.1 Statistical table of reads usage for assembly

5.2 Kmer level estimate and GC-depth analysis

5.3 Statistical for reads alignment to known bacterial genome database, RDP database, fungal genome database, human gut gene catalogue etc.

2.Advanced bioinformatics analysis

1. Species classification analysis and functional annotation

1.1 Gene prediction toward those contigs length ≥ 500 bp

1.2 Results statistics of species and functional annotation on predicted ORFs

1.3 Functional annotation of ORFs by blastP against databases (KEGG, eggNOG database)

1.4 Species annotation of ORFs

1.5 Calculation of the relative abundance of each ORF (Samples ≥ 2)

The following comparative analysis could be implemented on the basis of species (or OTU) information:

2. Primary comparative analysis:

2.1 Generate profiling table

2.2 Principal component analysis (Samples ≥ 3)

2.3 Cluster analysis (Samples ≥ 3)

3. Advanced comparative analysis (Sample groups ≥ 2 ; Samples in each Group ≥ 10):

3.1 Screening factors (Species or fuction) significantly correlated with sample grouping

3.2 Principal component analysis based on screened significant factors

3.3 Cluster analysis based on significant screened factors

3. Personalized analysis: We can also perform customized analysis to meet requirements of specific projects.