Computational meta-analysis of cervical cancer using available 16s rrna ngs data

Cervical cancer is one of the most frequently occurring and deadliest gynaecological cancer which develops in cervical cells. Since it develops in tissues lining the internal organs it is a Carcinoma. Human papilloma virus infection is found to top the list of carcinogenic factors. Overexpression of certain proteins due to HPV integration in host body over a time can result in carcinoma. However vaginal microbiota plays a key role in development, persistence and progression of infections leading to diseases such as cervical cancer. Some recent studies have revealed potential roles of microbiome in cervicovaginal diseases. Thus a comparative metagenomic study among such samples can uncover microbial diversities present in these samples. Due to presence of highly conserved regions as well as hyper variable regions 16s rRNA gene sequence is selected for identification and classification of bacterial diversity. For the purpose of metagenomic analysis 16s rRNA gene sequences were analysed using QIIME pipeline.