Putting Science to Work
Next Generation Sequencing (NGS)

NGS Data Analysis

Next Generation Sequencing (NGS)

We provide comprehensive high-throughput data analysis services. Our bioinformatics offerings include standard and highly customized data services along with biological interpretation if required. Our expertise includes but is not limited to the major next generational sequencing (NGS) workflows for DNA, RNA and small RNA, data mining, metadata overlay and biological contextualization, and network and pathway analysis. All workflow steps include data type specific alignment and QC, coupled with powerful Genome Browser explorations to enable visual validations.

Services provided:

  • Alignment against whole genome to against targeted regions, split read alignment, screening against databases to identify contaminants.
  • Variant calling in the form of SNPs/MNPs/Indels with local re-alignment and Base Quality Score Recalibration.
  • Variant analysis by annotating the variants using the public databases COSMIC, ClinVar, dbSNP, etc., multi-sample SNP comparison, SNP effect analysis with respect to coding and non-coding regions, Identification of damaging variants using Sift, Polyphen, MetaSVm, Mutation Taster, LTR, Mutation Assessor etc..
  • Structural Variants identification (Long Insertions, Deletions, Inversions and Translocations)
  • Copy Number Variant detection with GC bias correction and identification of normal cell contamination (incase of cancer samples).
  • Alignment against the transcriptome as well as against genome and transcriptome together. Identification of new genes and new exons.
  • Quantification with a variety of normalization methods, DESeq, Quantile, RPKM, RPM, FPKM etc. Partition based quantification allows considering partial matches and spliced reads.
  • Differential Expression and Splicing Analysis with detection of novel spliced junctions.
  • Gene Fusion detection.
  • Clustering and metadata overlay.
  • Sample-sample and entity-entity correlations.
Small RNA-Sequencing
  • Small RNA read alignment against genome.
  • Quantification of small RNA genes and mature RNA species.
  • miRNA target prediction using TargetScan, PicTar, TarBase, microRNA.org, PITA.
  • Alignment using Bismark, a methylation-specific aligner.
  • Context specific (CHH, CHG and CGH) methylation calling.
  • Inter and intra-sample methylation comparison.
  • Peak and Motif detection.
  • Methylation detection with Relative and absolute methylation scores.
  • Differentially methylated region analysis.

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