%0 Journal Article %A Robinson, Kelly %A Crabtree, Jonathan %A Mattick, John %A Anderson, Kathleen %A Dunning Hotopp, Julie %D 2017 %T Additional file 7: Figure S6. of Distinguishing potential bacteria-tumor associations from contamination in a secondary data analysis of public cancer genome sequence data %U https://springernature.figshare.com/articles/journal_contribution/Additional_file_7_Figure_S6_of_Distinguishing_potential_bacteria-tumor_associations_from_contamination_in_a_secondary_data_analysis_of_public_cancer_genome_sequence_data/4584724 %R 10.6084/m9.figshare.c.3673879_D5.v1 %2 https://ndownloader.figshare.com/files/7423225 %K Microbiome %K Cancer %K Batch effects %K Genome sequencing %K Cancer-associated bacteria %K Acinetobacter %K Pseudomonas %K Stomach adenocarcinoma %K Acute myeloid leukemia %X The proportion of bacterial read pairs for RNA-Seq (panel A), whole genome sequencing (WGS, panel B), and whole exome sequencing (WXS, panel C) for an individual stomach adenocarcinoma (STAD) sample are illustrated. The RNA-Seq data shows an enrichment of Proteobacteria that have low proportions in the WGS and WXS data. WGS and WXS sequencing methods resulted in a more diverse collection of bacterial read pairs with only minor differences between the two methods. (PDF 445 kb) %I figshare