Tools: R (TCGAbiolinks, SummarizedExperiment, DESeq2, clusterProfiler, org.Hs.eg.db, ggplot2, ggrepel, pheatmap), TCGA-COAD, OncoKB & Microsoft Excel
Outcome: Identified 8,930 DEGs (tumor vs. normal). OncoKB annotation revealed 124 oncogenes, 76 TSGs, and 25 dual-role genes among DEGs.
Prediction of deleterious nsSNPs and their effect on the human NOG gene
Tools: NCBI dbSNP, SIFT, SNPs & GO, PhD-SNP, PremPS, CUPSAT, ConSurf, AlphaFold, STRING, Missense3D and DynaMut2 Outcome: Identified and prioritised potentially pathogenic non-synonymous SNPs in the NOG gene using multiple in silico tools, highlighting variants associated with skeletal developmental disorders.
Outcome:From a total of ~16,250 variants annotated with Ensembl VEP and filtering based on predicted impact and computational pathogenicity predictions resulted in a shortlist of 33 (novel) candidate variants of interest
GWAS SNPs Annotation & Prioritisation
Tools:NHGRI GWAS Catalog, FUMA GWAS, Open Target and Pharos, Python (Pandas, os and csv) & R: (biomaRt, ggplot2, ggthemes, readxl, tidyr, data.table, dplyr, stringr & igraph) Outcome:IL13, IL4, IL4R, IL2RA, ORMDL3, GSDMB, ZPBP2, IKZF3, KIF3A, SMAD3, TLR1, RORA, RUNX3, LRRC32, C11orf30/EMSY, RAD50, TNFSF4 etc. have been found to have strong associations with Asthma. Majority of the genes are enriched in pathways, like- JAK-STAT Signalling Pathway and Hematopoietic cell lineage.