mc_datasets

Bioinformatic analyses of amplicon and shotgun datasets used for investigating MGS bias.

Pre-requisites

Dependencies

R packages

tidyverse
dotenv https://github.com/gaborcsardi/dotenv
rentrez is needed only if re-generating the sample metadata files
dada2
phyloseq
metaphlanr if planning to post-process Metaphlan2 output to a read table

Software

NCBI's SRA Toolkit for downloading sequence data
Metaphlan2 for microbiome profiling of shotgun data
(optional) Aspera's ascp program for faster downloading of sequence data

Environment file

A file called .env must be set up with various directory paths, which can be parsed by the R package dotenv. An example is in .env_example.

Usage notes

Sequence data and results will be stored in the path given by DATA_PATH in the .env file, with the following structure.

$DATA_PATH
|-- brooks2015
|   `-- final
|   `-- reads
|   `-- supplementary_files
|-- costea2017
|   `-- final
|   `-- intermediate
|   `-- reads
|   `-- supplementary_files
`-- sinha2017
    `-- reads
        `-- filtered

For each project, the raw sequence data is stored in the folder reads and the generated phyloseq objects will be stored in the folder final, with any intermediate analysis products a folder intermediate.

Datasets

brooks2015 (16S amplicon)

Brooks JP, Edwards DJ, Harwich MD, Rivera MC, Fettweis JM, Serrano MG, Reris RA, Sheth NU, Huang B, Girerd P, Strauss JF, Jefferson KK, Buck GA. 2015. The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies. BMC Microbiol 15:66.

costea2017 (shotgun)

Costea PI, Zeller G, Sunagawa S, Pelletier E, Alberti A, Levenez F, Tramontano M, Driessen M, Hercog R, Jung F-E, Kultima JR, Hayward MR, Coelho LP, Allen-Vercoe E, Bertrand L, Blaut M, Brown JRM, Carton T, Cools-Portier S, Daigneault M, Derrien M, Druesne A, de Vos WM, Finlay BB, Flint HJ, Guarner F, Hattori M, Heilig H, Luna RA, van Hylckama Vlieg J, Junick J, Klymiuk I, Langella P, Le Chatelier E, Mai V, Manichanh C, Martin JC, Mery C, Morita H, O’Toole PW, Orvain C, Patil KR, Penders J, Persson S, Pons N, Popova M, Salonen A, Saulnier D, Scott KP, Singh B, Slezak K, Veiga P, Versalovic J, Zhao L, Zoetendal EG, Ehrlich SD, Dore J, Bork P. 2017. Towards standards for human fecal sample processing in metagenomic studies. Nat Biotechnol 35:1069–1076.

fouhy2016 (16S amplicon)

Fouhy F, Clooney AG, Stanton C, Claesson MJ, Cotter PD. 2016. 16S rRNA gene sequencing of mock microbial populations- impact of DNA extraction method, primer choice and sequencing platform. BMC Microbiol 16:123.

sinha2015 (16S amplicon)

Sinha R, Abu-Ali G, Vogtmann E, Fodor AA, Ren B, Amir A, Schwager E, Crabtree J, Ma S, Abnet CC, Knight R, White O, Huttenhower C. 2017. Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium. Nat Biotechnol 35:1077–1086.

parras-molto2018 (viral, qPCR)

Parras-Moltó M, Rodríguez-Galet A, Suárez-Rodríguez P, López-Bueno A. 2018. Evaluation of bias induced by viral enrichment and random amplification protocols in metagenomic surveys of saliva DNA viruses. Microbiome 6:119.

mikemc/mc_datasets_backup