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Rewati Tappu

Former lab member







E-Mail: rewati-mukund.tappu at



I am interested in the analysis of genomic and metagenomic data produced using next-generation sequencing technologies. Development of sequence analysis pipelines for metagenomic datasets and their statistical and visual analysis is my main focus of research. 
Some of the projects I have been involved with are:
1. Analysis of the gut microbiome samples of obese patients undergoing a weight-loss formula diet intervention.
In this study, the fecal samples of obese patients that participated in a formula diet treatment were subjected to whole-genome shotgun metagenomic sequencing for six time-points. The time-points corresponded to the start of the intervention, the end of the intervention, and four time-points along the maintenance phase. We aimed at characterising the changes in the gut microbiota along the intervention, and whether the changes remain stable in the maintenance phase. We also aimed at determining whether the gut microbiota can be used as a predictor of the success of the diet-intervention.
2. Analysis of the correspondence between systems of functional classification.
In this project, we aim at comparing the different systems of functional classification like InterPro, KEGG, and eggNOG that are commonly employed in the analysis of metagenomic datasets.
3. Evaluation of the gene-centric assembler in MEGAN 6
The metagenomic analysis tool, MEGAN 6, can be employed to carry out a gene-centric assembly of the reads binned into a particular taxonomic or functional category. I am involved in testing the assembler across different genes and samples. 
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