https://github.com/vjcitn/bioccuratedccdg_anvil
Manage concepts related to PFB import from Gen3 to AnVIL; example of CCDG
https://github.com/vjcitn/bioccuratedccdg_anvil
Last synced: 3 months ago
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Manage concepts related to PFB import from Gen3 to AnVIL; example of CCDG
- Host: GitHub
- URL: https://github.com/vjcitn/bioccuratedccdg_anvil
- Owner: vjcitn
- Created: 2022-02-17T12:25:21.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-02-17T12:26:12.000Z (over 3 years ago)
- Last Synced: 2025-01-09T13:46:31.346Z (5 months ago)
- Size: 1.95 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# BiocCuratedCCDG_ANVIL
Manage concepts related to PFB import from Gen3 to AnVIL; example of CCDG
# AnVIL Workspace Description
## Concept
Given a PFB "export to terra" from Gen3, produce a DataFrame instance
that can be used as a 'sample metadata' resource for molecular data
lodged in the workspace.
Here are the fields of "sample" data from CCDG:
```
entity:sample_id pfb:created_datetime pfb:project_id pfb:sample_provider pfb:specimen_id pfb:state pfb:subject pfb:submitter_id pfb:updated_datetime
```
The function given below will take sample, subject, and sequencing tables and put them together with sample_id as the primary key.
## colData construction
```
build_colData = function() {
require(AnVIL)
require(dplyr)
simplify_names = function(.data) {
names(.data) = gsub("^pfb:", "", names(.data))
.data
}
samp = avtable(table="sample")
subj = avtable(table="subject")
seqtab = avtable(table="sequencing")
#alltypes = unique(samp$`pfb:tissue_type`)
#tissframes = lapply(na.omit(alltypes), function(x) samp |> filter(`pfb:tissue_type` == x))
#names(tissframes) = na.omit(alltypes)
#library(MultiAssayExperiment)
# by stages
#t2 = lapply(tissframes, function(x) mutate(x, subject_id=`pfb:subject`))
t3 = left_join(mutate(samp, subject_id=`pfb:subject`), subj, by="subject_id")
sqsq = mutate(seqtab, sample_id=`pfb:sample`)
inner_join(sqsq, t3, by="sample_id") |> simplify_names()
}
```
The result of running the above function in this workspace has fields:
```
> names(ccdg_full_coldata)
[1] "sequencing_id" "total_reads" "file_format" "project_id"
[5] "estimated_library_size" "data_format" "sequencing_assay" "mean_coverage_per_base"
[9] "date_data_generation" "data_type" "file_size" "md5sum"
[13] "experimental_strategy" "file_name" "submitter_id" "object_id"
[17] "file_state" "fragment_length_mean" "file_type" "duplication_rate_of_mapped"
[21] "data_category" "state" "reference_genome_build" "created_datetime"
[25] "ga4gh_drs_uri" "file_md5sum" "updated_datetime" "sample"
[29] "sample_id" "project_id.x" "submitter_id.x" "sample_provider"
[33] "state.x" "created_datetime.x" "specimen_id" "updated_datetime.x"
[37] "subject" "subject_id" "sex" "project_id.y"
[41] "participant_id" "submitter_id.y" "state.y" "dbgap_submission"
[45] "created_datetime.y" "dbgap_study_id" "updated_datetime.y" "project"
```