Last updated: 2022-05-12

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Knit directory: diamantopoulou-ctc-dynamics/

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Publication

Diamantopoulou, Z., Castro-Giner, F., Schwab F.D., Foerster C., Saini, M., Budinjas, S., Strittmatter, K., Krol, I., Seifert, B., Heinzelmann-Schwarz, V., Kurzeder, C., Rochlitz, C., Vetter, M., Weber, W.P., & Aceto N. The metastatic spread of breast cancer accelerates during sleep. Nature, 2022.

Abstract

We isolated live circulating tumor cells (CTCs) from a breast cancer patient (number of CTCs = 36) and two breast cancer xenografts, NSG-CDX-BR16 (number of CTCs = 138) and NSG-LM2 (number of CTCs = 108) at different time points. Isolated CTCs were categorized into three different types : single CTC, CTC clusters and CTC-white blood cells (CTC-WBC) clusters. Amplified cDNA was prepared according to the Smart-seq2 protocol. Libraries were prepared using with Nextera XT (Illumina) and sequenced on Illumina NextSeq500 instrument in 75-bp single-read mode.

Data pre-processing

Raw data is available at Gene Expression Omnibus (GEO, NCBI; accession number GSE180097). Data processing is computationally expensive and is not covered in this repository. We provide description of the data pre-processing workflow together with software version in the original publication. Processed data, large result files, additional functions, references and metadata are were archived at DOI

Data and code availability

To reproduce our analysis, first clone source code from the GitHub repository. This repository is also archived at DOI

git clone https://github.com/TheAcetoLab/diamantopoulou-ctc-dynamics.git

Next, download processed data deposited in Zenodo into the cloned project folder ./data directory and untar the files.

for file in *.tar.gz; do tar xzvf "${file}" && rm "${file}"; done

Reproducibility

The results form our analyses are listed below in webpage format. They were generated from R Markdown documents deposited in the GitHub repository. The workflow of the analysis was created using the workflowr R package and can be reproduced in its totality using workflowr wflow_build command after the installation of the proper R packages. Session info, including R and package versions, was automatically included at the end of each analysis file.

Files containing pre-computed results from differential expression or gene-set enrichment analyses were deposited in DOI. In order to generate those files again change the option eval = FALSE to eval = TRUE in the specific code chunk from the R Markdown file.