| Genome Sequencing |
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| de novo sequencing |
Re-sequencing |
Exome Sequencing |
| Basic information of genome |
Basic information of genome |
Align the clean reads with reference genome |
| Genome assembling results |
Assembly of consensus sequences |
Histogram of depth distribution in target regions |
| Genome assembling results evaluation |
SNP detection |
Evenness of exome capture sequencing |
| Genome annotation results |
Indel detection |
Consensus genotypes calling in exome |
| Comparative genomics and evolution analysis |
Structure variation detection |
Depth and coverage of each CCDS exome |
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Annotation of the resulting SNPs |
| Transcriptome Sequencing |
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| RNA-Seq Analysis |
Digital Gene Expression (DGE) |
Small RNA analysis |
| de novo transcriptome |
Sequencing and basic data processing |
Sequencing and basic data processing |
| Sequencing and basic data processing |
Experimental repeatability analysis |
Length distribution of small RNAs |
| Build Unigene |
Saturation analysis |
Mapping small RNA sequence to genome |
| Function annotation of Unigene |
Mapping tags to genes |
Identification of microRNAs based on miRBase |
| Enriched GO categories of Unigene |
Screening of differentially expressed genes |
Identification of small RNAs |
| Differentially expressed Unigene |
Expression pattern analysis of DEGs |
Identification of repeat-associated small RNAs |
| Protein function prediction and classification |
GO functional enrichment analysis of DEGs |
Identification of degraded fragments of mRNA |
| RNA Seq with reference genome |
Pathway enrichment analysis of DEGs |
Annotation and classification of small RNAs |
| Sequencing and basic data processing |
Protein-protein interaction network analysis |
Novel microRNAs structure prediction |
| Summary of data output and alignment |
Antisense transcripts detection |
MicroRNA expression profile |
| Gene coverage and sequencing depth |
New transcripts detection |
Differential expression of microRNAs |
| Differentially expressed genes |
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Cluster analysis or expressed microRNAs |
| Optimization of gene structures |
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MicroRNA target prediction |
| Identification of alternative spliced transcripts |
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| Identification of novel genes |
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| Identification of gene tranlocations and fusions |
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| Microbial Genome Sequencing |
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| Bacterial Genome Sequencing |
Fungal Genome Sequencing |
Metagenome Sequencing |
| Genome assembly |
de novo analysis |
16S rRNA analysis |
| Gene annotation |
Re-sequencing analysis |
Metagenome analysis (EGTs analysis) |
| Gene functional annotation |
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Metagenome analysis (Short-reads analysis) |
| Synteny analysis and gene family analysis |
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Metatranscriptome analysis |
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Multi-sample comparative analysis |
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KEGG pathway analysis |
| Epigenome Sequencing |
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Bio-Cloud Computing |
| ChIP-Seq |
Bisulfite Sequencing |
Computing and Storage Services |
| Basic bioinformatics analysis |
Basic bioinformatics analysis |
Cluster computing |
| Map ChIP-Seq reads to reference |
Map bisulfite-seq reads to reference |
Cloud computing |
| Upload the data into Genome browser |
Get the methylation profile of the mapped reads |
Storage service (NGS raw data, Research results) |
| Genome-side scanning to identify enriched regions |
Gather the methylation profile of the mapped reads |
Training for Server Managers |
| The fraction of mapped reads in genome |
Get the methylation rate of all methylated C in CpG |
Training on Bioinformatics Technology |
| Distribution of peak depth in gene region |
Get the methylation rate of all dispersed C |
Construction of Genome Database |
| The genes overlapped by peaks for each sample |
Methylated CpG in different gene regions |
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| GO functional enrichment analysis of the genes |
Methylated dispersed C in different gene regions |
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| Difference analysis for the genes with different peak depth |
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| Formation up a Bigtable.txt file containing all the information |
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