Nutritional Lung Immunity

A description of the monocyte derived dendritic cell bioinformatics pipelines.

In vitro time-series RNAseq data from monocyte derived dendritic cells exposed to A. fumigatus conidia (Experiment DCcocultAF).

Description: Monocyte derived dendritic cells from six different human donors (IL-4/GM-CSF differentiated) were exposed to Aspergillus fumigatus conidia with cell:conidia ratio=1:1 for 0, 2, 4, 6, 8 hours. Purity of dendritic cells was confirmed by flow cytometry using CD14-/Cd1a+/HLA+/CD83+. For more details, go to the experimental section for monocyte derived DCs and see the section for (Experiment DCcocultAF).

Preprocessing pipeline

The FASTQ files were aligned using a custom Nextflow pipeline for preprocessing of data and alignment of reads against the GRCh38 reference genome version 96. An overview of the pipeline is below. Click on the image to be taken to the Github repository containing the Nextflow pipeline.

Postprocessing analysis

Differential Expression Github Repository

Contains R scripts for performing differential expression analysis of DCs exposed to A. fumigatus and control DCs using DESeq2.

Processed Data

Contains post-processed data such as aligned read counts and quality control after alignment trimming.

References

Preprocessing tools

  • Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A Flexible Trimmer for Illumina Sequence Data. Bioinformatics, 30(15), 2114–2120. https://doi.org/10.1093/bioinformatics/btu170
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: Summarize Analysis Results for Multiple Tools and Samples in a Single Report. Bioinformatics, 32(19), 3047–3048. https://doi.org/10.1093/bioinformatics/btw354
  • García-Alcalde, F., Okonechnikov, K., Carbonell, J., Cruz, L. M., Götz, S., Tarazona, S., Dopazo, J., Meyer, T. F., & Conesa, A. (2012). Qualimap: Evaluating next-Generation Sequencing Alignment Data. Bioinformatics, 28(20), 2678–2679. https://doi.org/10.1093/bioinformatics/bts503
  • Tommaso, P. D., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow Enables Reproducible Computational Workflows. Nature Biotechnology, 35(4), 316–319. https://doi.org/10.1038/nbt.3820

Postprocessing tools

  • Love, M. I., Huber, W., & Anders, S. (2014). Moderated Estimation of Fold Change and Dispersion for RNA-Seq Data with DESeq2. Genome Biology, 15(12). https://doi.org/10.1186/s13059-014-0550-8