Bioinformatics Analysis

    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 Variants etc.) 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

    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 (more than 2 samples)

    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

    BGC

    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 (more than 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

    Proteome Analysis

    1. Proteome analysis of gel spots and bands

    2. Proteome analysis of pull downs

    3. Proteome analysis of complex samples

    4. Differential proteome analysis

    5. Phospohoproteomic analysis