The goal of AnalyteExplorer is to pre-process data for the AnalyteExplorer
module in ImmuneSpace.
You can install the development version of AnalyteExplorer from GitHub with:
# install.packages("remotes")
remotes::install_github("RGLab/AnalyteExplorer")
library(AnalyteExplorer)
library(UpdateAnno)
options(debug_dir = tempdir())
labkey.url.base <- "https://datatools.immunespace.org"
labkey.url.path <- "/AnalyteExplorer"
genes <- process_data("genes")
validate(genes)
res <- update_table(genes)
cohorts <- process_data("cohorts")
validate(cohorts)
res <- update_table(cohorts)
btm <- process_data("blood_transcription_modules")
validate(btm)
res <- update_table(btm)
signatures <- process_data("gene_signatures")
validata(signautres)
res <- update_table(signatures)
summaries <- process_data("gene_expression_summaries")
validate(summaries)
res <- update_table(summaries)
- Based on Molecular signatures of antibody responses derived from a systems biological study of 5 human vaccines
- The function updates the gene symbols with Hugo.
- This table is used to display metadata about the selected module in the app.
id | name | genes | matched_gene_ontology_terms | number_of_genes | module_category |
---|---|---|---|---|---|
M0 | targets of FOSL1/2 (M0) | CCL2, COL1A2, DCN, IL6, CXCL8, LIF, MGP, MMP1, MMP2, MMP9, PLAU, THBD | extracellular space (11), extracellular region (11), protein binding (9) | 12 | TF targets |
M1.0 | integrin cell surface interactions (I) (M1.0) | COL1A1, COL1A2, COL5A1, DPYSL3, MYH10, NRP1, PTK2, RHOC, RRAS, SEMA6A | protein binding (26), axon guidance (20), extracellular region (16) | 29 | molecular function |
M1.1 | integrin cell surface interactions (II) (M1.1) | AHSP, ALAD, ALAS2, CPOX, E2F2, FECH, GATA1, HEMGN, HMBS, PLEK2, TMOD1 | protein binding (12), extracellular region (12), extracellular matrix structural constituent (9) | 12 | molecular function |
M2.0 | extracellular matrix (I) (M2.0) | CD1D, HLA-DMA, HLA-DMB, HLA-DPA1, HLA-DPB1, HLA-DQA2, METTL7A, WDFY4 | protein binding (27), extracellular region (26), extracellular matrix (21) | 30 | location |
- This function creates a gene expression table by cohort, timepoint, and analyte type (gene, blood transcript module, or gene signature).
- Processing steps:
- Fetch gene expression matrices and metadata from ImmuneSpace and combine them into one
ExpressionSet
object.- Remove genes that are not available in all expression matrices.
- Remove samples that have negative timepoint and select one timepoint if sample has multiple baseline timepoints.
- Create gene expression table summarized by analyte type.
- In sample level, when summarizing by blood transcript module or gene signature, compute geometric mean of the expression values of the genes in the module or signature
- In cohort level, compute the fold change of the expression values for all combinations of timepoints comparing to the baseline timepoint.
- Compute mean and standard deviation of those fold change values by analyte type
- Merge the three summarized tables
- Fetch gene expression matrices and metadata from ImmuneSpace and combine them into one
cohort | sample_type | study_accession | condition | timepoint | analyte_id | analyte_type | mean_fold_change | sd_fold_change | id |
---|---|---|---|---|---|---|---|---|---|
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 0 | A1CF | gene | 0 | 0 | 1 |
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 0 | A2M | gene | 0 | 0 | 2 |
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 3 | M0 | blood transcription module | -0.0385090 | 0.0875805 | 3894315 |
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 3 | M1.0 | blood transcription module | -0.0181510 | 0.1051648 | 3894316 |
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 3 | 21357945_1_8 | gene signature | 0.7102219 | 0.5402085 | 4028003 |
healthy aldults | Whole blood | SDY1529 | Yellow_Fever | 3 | 21357945_2_9 | gene signature | 0.1105955 | 0.5026520 | 4028004 |