BiocProject: a Bioconductor-oriented project management package

# BiocProject: a Bioconductor-oriented project management package

Nathan Sheffield, Michal Stolarczyk

<span style="font-size:0.6em"><a href="http://www.databio.org/slides">www.databio.org/slides</a></span>

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### Outline

<div class="previewblock" style="width:40%">Motivation for PEPs</div>
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<div class="previewblock" style="width:60%">Demonstration of BiocProject</div>

<div class="questionblock" style="background:#222; color:#eee; font-size: 0.6em; margin-top: 35px">&#9665; Questions &#9655;</div>
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## Most workflows require individual metadata organization

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## What if?

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## The solution

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## The solution

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## PEP: A standard format for project metadata

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## PEP Ecosystem

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## <img src="/shorts/short-biocproject/pep_logo.svg" width="70" style="vertical-align: middle;"> PEP format

<span class="bullet"><img src="/shorts/short-biocproject/icons/file.svg" width="30" class="bullet"> project_config.yaml</span>

```yaml
metadata:
  sample_annotation: /path/to/samples.csv
  output_dir: /path/to/output/folder
```

---

<span class="bullet"><img src="/shorts/short-biocproject/icons/file.svg" width="30" class="bullet"> samples.csv</span>

```csv
sample_name, protocol, organism, data_source
frog_0h, RNA-seq, frog, /path/to/frog0.gz
frog_1h, RNA-seq, frog, /path/to/frog1.gz
frog_2h, RNA-seq, frog, /path/to/frog2.gz
frog_3h, RNA-seq, frog, /path/to/frog3.gz
```

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## BiocProject integrates PEP into Bioconductor

It provides:
- automated data loading
- functions for interacting with project metadata
- PEP-annotated Bioconductor data objects

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## Install

```
devtools::install_github(repo='pepkit/pepr')
devtools::install_github(repo='pepkit/BiocProject')
```

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## Load an example PEP with bioconductor section

Here's a demo included with the package:

```
metadata:
  sample_table: sample_table.csv
bioconductor:
  readFunName: readBedFiles
  readFunPath: readBedFiles.R
```

`readFunName` is an R function that reads in your PEP.
`readFunPath` is an R file that contains your function

---

## sample_table

| sample_name | file_path |
|-------------|-----------|
| laminB1Lads | data/laminB1Lads.bed |
| vistaEnhancers | data/vistaEnhancers.bed |

---

## readBedFiles.R

```
readBedFiles = function (project) {
    cwd = getwd()
    paths = pepr::samples(project)$file_path
    sampleNames = pepr::samples(project)$sample_name
    setwd(dirname(project@file))
    result = lapply(paths, function(x) {
        df = read.table(x)
        colnames(df) = c("chr", "start", "end")
        gr = GenomicRanges::GRanges(df)
    })
    setwd(cwd)
    names(result) = sampleNames
    return(GenomicRanges::GRangesList(result))
}
```

---

```
library(BiocProject)
configFile = system.file("extdata", "example_peps-master", 
  "example_BiocProject", "project_config.yaml",
  package = "BiocProject")
bp = BiocProject(file=configFile)
#> Loaded config file: .../example_BiocProject/project_config.yaml
#> The 'bioconductor' key found in the Project config
#> Used function 'readBedFiles' from the environment
```

---

```
bp = BiocProject(file=configFile)
bp
#> GRangesList object of length 2:
#> $laminB1Lads 
#> GRanges object with 1302 ranges and 0 metadata columns:
#>          seqnames              ranges strand
#>      [1]     chr1   11401198-11694590      *
#>      [2]     chr1   14877629-15246452      *
#>      [3]     chr1   18229570-19207602      *
#>      [4]     chr1   29618442-31162049      *
#>      [5]     chr1   33943885-35623392      *
#>      ...      ...                 ...    ...
#>   [1298]     chrX 154066672-154251301      *
#>   [1299]     chrY     2880166-7112793      *
#>   [1300]     chrY   15047033-15333970      *
#>   [1301]     chrY   15603977-16627892      *
#>   [1302]     chrY   16966225-21013116      *
#> 
#> ...
#> <1 more element>
#> -------
#> seqinfo: 24 sequences from an unspecified genome; no seqlengths
#> 
#> metadata: PEP project object. Class:  Project
#>   file: example_BiocProject/project_config.yaml
#>   samples:  2
```

---

```
samples(bp)
#>       sample_name               file_path
#> 1:    laminB1Lads    data/laminB1Lads.bed
#> 2: vistaEnhancers data/vistaEnhancers.bed
```

---

```
config(bp)
#> Config object. Class: Config
#>  metadata:
#>     sample_table: example_BiocProject/sample_table.csv
#>  bioconductor:
#>     readFunName: readBedFiles
#>     readFunPath: example_BiocProject/readBedFiles.R
#>  name: example_BiocProject
```

---

## BiocProject in action
## Zero to hero in 3 lines of code

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1. Create a PEP:

```
geofetch -i GSE129383 -P /pepatac/pipeline_interface.yaml
...
Finished processing 1 accessions
Creating complete project annotation sheets and config file...
  Sample annotation sheet:${SRAMETA}/GSE129383/GSE129383_annotation.csv
  Sample subannotation sheet:${SRAMETA}/GSE129383/GSE129383_subannotation.csv
  Config file: ${SRAMETA}/GSE129383/GSE129383_config.yaml
```

This downloads raw data and creates your PEP.

---

2. Run the PEPATAC ATAC-seq pipeline:

```
looper run GSE129383_config.yaml --sp sra_convert
looper run GSE129383_config.yaml
```

This runs PEPATAC on your newly-created PEP.

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3. Load processed data into R with BiocProject:

```
bp = BiocProject::BiocProject("GSE129383_config.yaml")
bp
```

This loads your bed files into R.

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### Conclusion

- PEP is a language-agnostic standard *project* representation.
- BiocProject loads metadata and data for a PEP into R
- Add in `geofetch`, `looper`, and `PEPATAC` to connect raw data through analysis

More information at [pepkit.github.io](http://pepkit.github.io/); [code.databio.org/BiocProject](http://code.databio.org/BiocProject).

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## Acknowledgments

**Sheffield lab**
- Ognen Duzlevski
- Jianglin Feng
- Aaron Gu
- Kristyna Kupkova
- John Lawson
- Vince Reuter
- Jason Smith
- **Michal Stolarczyk**

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**Bioconductor**
- Levi Waldron
- Sean Davis

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**Funding:**

NIGMS 1R35GM128636

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