TCGA Microbial Content

Comprehensive analysis of microbial content in 5,734 whole-genome sequencing samples from The Cancer Genome Atlas project

These are the supplementary files and tables for our bioRxiv preprint [1] We are posting the files here because some of them are too large for the journal to take as supplements.

Supplementary Tables Captions

1. Table S1. Raw counts of 5,734 TCGA WGS samples classified at the species level against the Kraken Microbial2023 database, excluding eukaryotes. The contents of Microbial2023 are described in the main text. This resulted in 11,332 species that have non-zero counts.
2. Table S2. Normalized counts of the values in Table S1, converted to counts per million reads sequenced.
3. Table S3. Normalized counts of the values in Table S1, converted to reads per kilobase of genome per million reads sequenced.
4. Table S4. Raw counts of 5,734 TCGA WGS samples classified at the species level against Fungi_RefSeq database. The contents of Fungi_RefSeq include all 557 fungal species in RefSeq as of late 2023.
5. Table S5. Normalized counts of TableS4, converted to counts per million reads sequenced.
6. Table S6. Normalized counts of TableS4, converted to reads per kilobase of genome per million reads sequenced.
7. Table S7. Raw counts of 18 selected viruses identified in each of 5,734 TCGA WGS samples by the TCGA project. The TCGA filtering process used bwa to align reads against a database including the human genome plus multiple strains of human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV-1 1, and HCV-2), and cytomegalovirus (CMV). Counts here include the 14 strains of HPV most often associated with cancer: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68. Unlike the counts from Kraken2, which treated paired reads as a unit, paired reads were counted separately here; thus if both reads in a pair aligned, this was counted as 2 matches. Note that unlike the KrakenUniq database, low-complexity sequences were not masked out prior to alignment, which might have yielded many false-positive matches for some viruses.
8. Table S8. TCGA study abbreviations.
9. Table S9. Raw counts of 4,550 TCGA WGS samples classified at the genus level against Microbial2023 database, for samples used in both this study and in the Poore et al. study. This dataset contains counts for all 3,552 genera that had non-zero counts in either study.
10. Table S10. Raw counts from the Poore et al. study at the genus level, for samples used in both this study and Poore et al. This set contains 4,550 samples and 3,552 genera. Raw counts included here were taken directly from Poore et al. (2020).
11. Table S11. Raw counts of TCGA WGS samples classified at the species level against the Fungi_RefSeq database, for samples and species matched with the Narunsky-Haziza et al. study. This resulted in 4,271 samples and 224 species.
12. Table S12. Raw counts from the Narunsky-Haziza et al. study at the species level, for samples and species matched with this study. This resulted in 4,271 samples and 224 species. Raw counts included here were taken directly from Narunsky-Haziza et al. (2022).
13. Table S13. TCGA metadata for 5,734 samples, including unique IDs for this study, IDs used by Poore et al., IDs used by Narunsky-Haziza et al., and the original TCGA identifiers, followed by read length (rd_len), the total number of reads that TCGA reported as aligned to GRCh38 (tot_aln), the number of reads that failed to align to GRCh38 (grch38_unmapped), and the number of reads that failed to align to both GRCh38 and CHM13 (grch38+chm13_unmapped). Counts represent individual read counts; paired-end reads will count as 2 reads each.
14. Table S14. List of species in the Microbial2023 Kraken database, with RefSeq accessions.
15. Table S15. List of species in the Fungi_RefSeq Kraken database, with RefSeq accessions.
16. Table S16. RefSeq v200 to v220 name conversion list, for 14 of the 557 fungal species whose names were changed between the two releases of RefSeq.

Citation

1. Ge, Y., Lu, J., Puiu, D., Revsine, M., & Salzberg, S. L. (2024). Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project. bioRxiv, 2024-05.

Updates

1. 19 August 2024: we have updated Table S1-3 and S9-10 by removing raw counts related to HPV, HBV/HCV, and CMV, and added Table S7 separately for those viral counts.