Whole genome sequence data analysis

1. Quality control of raw reads

2. Preprocessing of the raw reads

3. Unspliced mapping of the preprocessed reads onto a reference genome

4. Post-alignment processing

5. Quality control of the mapped reads

6. Variant calling

7. Variant annotation

8. Variant filtering and prioritisation

Reference based Transcriptome analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Mapping of transcripts against reference genome

4. Identification and quantification of transcript

5. Transcript annotation

6. Identification of SSRs, SNPs, isoforms and alternative transcripts

7. Identification of novel and rare transcripts

8. Gene Ontology and pathway analysis

9. Differential gene expression analysis (>2 samples)

Genome Resequencing analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Alignment of reads against Reference Genome: mapping statistics and graphs

4. Variant (SNPs, InDels, Structural Variantsetc.) detection

5. Variant annotation

6. Identification of novel variants

7. Comparative analysis (more than 2 samples)

Genome de novo analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Assembly of reads into contigs and Scaffolds

4. Genome assembly statistics

5. Gene prediction

6. Gene annotation

7. Gene ontology, functional classification of genes in biological process, cellular components and molecular functions

8. Genome wide SSRs identification

9. Phylogenetic analysis

Exome analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Alignment of reads against Reference Genome: mapping statistics and graphs

4. SNPs and InDels calling

5. SNPs and InDels annotation

6. Gene Ontology

De novo Transcriptome analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. De novo assembly of transcripts to contigs/ Scaffolds

4. Coding region prediction

5. Coding region annotation

6. Identification of SSRs and SNPs

7. Identification of isoforms and alternative splice sites

8. Gene Ontology and pathway analysis

9. Gene expression profiling

Metagenome analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Assembly

4. Phylogenetic analysis and taxonomic classification

5. Gene prediction and functional annotation

6. Pathway analysis

7. Abundance estimation

8. Comparative analysis (more than two samples)

9. Principle component analysis

Amplicon analysis(16S rRNA, ITS etc.,)

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. OTUs (Operational Taxonomic Units) identification

4. Taxonomic and phylogenetic analysis

5. Diversity and rarefaction analysis

Metatranscriptome analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Assembly

4. Phylogenetic analysis and taxonomic classification

5. Identification and annotation of coding region

6. Functional annotation

7. Pathway analysis

8. Gene expression diversity analysis

9. Differential gene expression analysis (> 2

samples)

Target Sequencing analysis

1. Raw Reads: Quality and Statistics

2. Filtered Reads: Quality and Statistics

3. Alignment of reads against reference genome:mapping statistics and graphs

4. Variant calling

5. Variant annotation and effect prediction

6. Variant filtering

7. Identification of novel and rare variation