Distinguishing potential bacteria-tumor associations from contamination in a secondary data analysis of public cancer genome sequence data

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• 作者：Kelly M. Robinson ; Jonathan Crabtree ; John S. A. Mattick…
• 关键词：Microbiome ; Cancer ; Batch effects ; Genome sequencing ; Cancer ; associated bacteria ; Acinetobacter ; Pseudomonas ; Stomach adenocarcinoma ; Acute myeloid leukemia
• 刊名：Microbiome
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：5
• 期：1
• 全文大小：2495KB
• 刊物主题：Medical Microbiology; Bioinformatics; Microbial Ecology; Microbiology; Microbial Genetics and Genomics; Virology;
• 出版者：BioMed Central
• ISSN：2049-2618
• 卷排序：5

文摘

BackgroundA variety of bacteria are known to influence carcinogenesis. Therefore, we sought to investigate if publicly available whole genome and whole transcriptome sequencing data generated by large public cancer genome efforts, like The Cancer Genome Atlas (TCGA), could be used to identify bacteria associated with cancer. The Burrows-Wheeler aligner (BWA) was used to align a subset of Illumina paired-end sequencing data from TCGA to the human reference genome and all complete bacterial genomes in the RefSeq database in an effort to identify bacterial read pairs from the microbiome.