BIOINFORMATICSOFFERINGS

Now a day’s, pharma research is facing challenges in

deciphering molecular understanding of disease initiation,

progress and establishment as well as performance

assessment of drug molecule on such phases of disease

development. Emerging of next generation sequencing

bases molecular tools were found to be a key method for

creating genome wide genomics landscape of gene

mutations, gene expression and gene regulation events.

Although NGS is a powerful tool for molecular research but

same time it have its own technical challenges. Few major

challenges of NGS based pharmacogenomics is

summarized below -

Pharmaceutical GENOMICS CHALLENGES

Large size genomic data

Deployment of rapidly updating

annotation databases

Analysis and Interpretation of Output

generated at each analytic phase

Integration of external information/

data to evaluate the hypothesis

Selection of appropriate analysis

tools or pipeline

Incedo’s Bioinformatics BASED ANALYTIC SOLUTIONSDespite various challenges offered by NGS data generated from pharmaceutical industries, the

bioinformatics methods supported by advanced computing infrastructure have made clinicians

capable to process, analyze, interpret and validate the hypothesis. Simultaneous growth of molecular

and computing environment made it possible to deliver outputs to pharmacogenomics needs. Our

bioinformatics based analytic solutions are as follows:

Cloud based scalable computing environment and parallel sample processing scalable in terms of RAM, computing and storage

Benchmarking of tools and pipelines crucial to ensure the accuracy and reproducibility of analytical tools and pipelines used to characterize NGS data

Proper and elaborated reporting of

results derived from each analysis at

different analytics phase

Evaluation of hypothesis in the light of

scientific literature by automated

algorithm and manual curation

Unique OFFERINGS

Results validation

with published research studies or data – Results

validation with cited literature

Wide range of analytics

tools

Secondary analysis

Tertiary analysis

Results validation with

published research studies

or data

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Gene Mu

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ChIP-SeqDNAse-SeqFAIRE-Seq

RNA-SeqMicroarray

Exome-SeqWGS-Seq

Targeted -Seq

Case Study Exome-Seq: We studied Exome

sequencing analysis on colon tumor tissue of 10

colorectal cancer patients. Genome-wide

assessment of the mutation events in these colon

tumors revealed massive alterations throughout

the genome, consisting of previously-established

and novel mutations. We found out the quality

assessment revealed high-quality of the

sequencing experiments. A large number (average

84%) of high-quality reads were perfectly aligned

with the human genome. Total 1330867 variants

were identified in the colon cancer samples out of

which 1078123 (81%) were known mutants and the

remaining 252744 were considered novel variants

specific to the colon cancer samples of this study.

Case Study ChIP-Seq: We evaluated the possible

role of transcription factors in the development

and progress of colon cancer disease. Co-

immunoprecipitation method elucidated a

comparison of genome-wide transcriptional

activity in a diseased state in comparison with

diseased vs. normal tissue. This study has been

derived from publicly- available colon cancer ChIP-

Seq repository data (PRJNA155759) entitled as

“Epigenomic enhancer profiling defines a signature

of colon cancer [ChIP-seq]”. It is largely focused on

coding sequences and promoters, despite the fact

that distal regulatory elements play a central role in

controlling transcription patterns. Histone mark

H3K4me1 was used to analyze gain and loss of

enhancer activity genome- wide in primary colon

cancer lines relative to normal colon crypts.

Representative WORKS

Representative WORKS

Case study of RNA-Seq of TCGA breast cancer data

of ER+, PR+, HER+, TNBC, Breast Tumor: We

downloaded Breast cancer data from TCGA and

used RNA-Seq Version 2 sequencing data to

determine gene expression levels from the TCGA

data portal. After analyzing around 1200 RNA-Seq

Samples we grouped the samples based on ER+,

PR+, HER2+, Triple Negative & Solid breast tumor

samples. The gene expression profile was measured

experimentally using the Illumina HiSeq 2000 RNA

Sequencing platform at the University of North

Carolina TCGA genome characterization center. We

have utilized MapSplice to perform the alignment

and RSEM to perform the gene level quantitation.

Level 3 interpreted data was also downloaded from

University of North Carolina TCGA genome

characterization data coordination center for

reference. Genes are mapped onto the human

genome coordinates using UCSC cgData HUGO

probeMap. This dataset shows gene-level

transcription estimates, as RSEM normalized

counts, percentile-ranked within each sample.

Incedo Inc. (formerly a part of $ 4Bn Indiabulls Group)

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INDIA: | 248, Udyog Vihar Phase-IV, Gurgaon - 122 015 | Tel: +91 124 4345900/ 01/ 02