tb /

Filename Size Date modified Message
tb_dashboard
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Ignore generated png and pdf files.
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Add LICENSE file.
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Update README.
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Confirm genotype results have SNPs in response eQTL exons.
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Compare different methods to remove batch effects: lm,
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Update joint analysis seeds and motif ordering based on batch-corrected
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Clean up bestmotif.R.
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Update aesthetics of boxplots in Figures 3 and 4.
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Fixed typo.
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Added R scripts for organizing fastq files, mapping reads, and counting reads per gene.
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Update aesthetics of Figure 1:
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Update GO analysis so that do not need to re-run so much Cormotif and
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Update GO analysis so that do not need to re-run so much Cormotif and
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Remove gridlines from Figures 5A and 5B.
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Put common knitr options in external file to be sourced. Cleaned up chunk options across main files.
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Added R scripts for organizing fastq files, mapping reads, and counting reads per gene.
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Added R scripts for organizing fastq files, mapping reads, and counting reads per gene.
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Mapped shape aesthetic to infection status to highlight controls in PCA that demonstrates PC2 is correlated with timepoint.
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Update table numbers.
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Update phagosome maturation genes to display in supplemental figure.
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Remove gridlines from Figure 2B.
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Deleted functions.R since most of the functions used in previous
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Remove gridlines from Figures 5A and 5B.
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Renumber Supplementary Figures to match final order in paper.
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Save PCA comparison to Tailleux et al. 2008 to pdf.
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Obtain the md5sum for table-s1.txt, the gene expression matrix.
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Update paths for GEO transfer files such that they are run from the code
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Create boxplots for genes mentioned in paragraph about vitamin D.

Mycobacterial infection induces a specific human innate immune response

This repo contains the code for the following manuscript:

Blischak, J. D. et al. Mycobacterial infection induces a specific human innate immune response. Sci. Rep. 5, 16882; doi: 10.1038/srep16882 (2015).

Other links related to this publication:

Description

We have collected gene expression data from macrophages isolated from six individuals. They were infected with different strains of Mycobacterium tuberculosis and other bacteria (nine total "conditions" including infections and controls). Furthermore, we collected data at 4, 18, and 48 hours post-infection.

Main analysis files

  • differential-expression.Rmd - Performs DE analysis with limma/voom.

  • joint_analysis.Rmd - Runs Cormotif to classify genes according to their expression patterns across the infections.

  • candidate_genes.Rmd - Plots expression of immune response genes.

  • reQTL.Rmd - Compares FDRs from DE analysis of response eQTL-associated genes (identified in Barreiro, Tailleux et al. 2012) to the background of expressed genes.

Preprocessing steps

Uses R package ngspipeline.

Sort files

./organize_files.R ../data/flow-cells.csv ../samples/

Map reads

find ../samples/ -name "*fastq.gz" -exec bash -c \
'echo "./map_fastq.R {} ~/subread-indexed-genomes/hg19/hg19" | \
qsub -l h_vmem=16g,bigio=1 -V -N map-`basename {}` -cwd -o stdout -e stderr' \;

Count reads per gene

mkdir std-counts
find ../samples/ -name "*bam" -exec bash -c \
'echo "./count_reads.R -sl ../data/gene_lengths.txt {} ../data/exons.txt -o /KG/jdblischak/counts" | \
qsub -l h_vmem=8g -V -N count-`basename {}` -cwd -o std-counts -j y' \;

Combine annotation and gene counts

library(ngspipeline)
anno  <-  "../data/annotation.txt"
count_files <- list.files("/KG/jdblischak/counts/",
                          pattern = "counts$", full.name = TRUE)
out_name <- "../data/counts_per_run.txt"
add_anno_to_counts(anno, count_files, out_name)

Sum gene counts per sample

library(ngspipeline)
sum_counts_per_sample("../data/counts_per_run.txt",
                      "../data/counts_per_sample.txt")

License

The code is available via the GPLv3 license (because we use multiple R/Biocodncutor packages which are GPL'd). The text is available via the CC BY 3.0 license.