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https://github.com/ShixiangWang/DoAbsolute
:package: Automate Absolute Copy Number Calling using 'ABSOLUTE' package
https://github.com/ShixiangWang/DoAbsolute
absolute copy-number-variation firehose
Last synced: about 2 months ago
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:package: Automate Absolute Copy Number Calling using 'ABSOLUTE' package
- Host: GitHub
- URL: https://github.com/ShixiangWang/DoAbsolute
- Owner: ShixiangWang
- License: other
- Created: 2019-01-07T10:39:28.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-11-28T03:13:40.000Z (10 months ago)
- Last Synced: 2024-05-11T10:31:45.812Z (4 months ago)
- Topics: absolute, copy-number-variation, firehose
- Language: R
- Homepage:
- Size: 2.5 MB
- Stars: 35
- Watchers: 1
- Forks: 12
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
- AwesomeGenomics - DoAbsolute
README
---
output: github_document
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# DoAbsolute
[](https://www.tidyverse.org/lifecycle/#stable)
[](https://github.com/ShixiangWang/DoAbsolute)
[](https://hits.seeyoufarm.com)
The goal of **DoAbsolute** is to automate ABSOLUTE calling for multiple
samples in batch-processing.
> **Running this tool with 1 thread (default setting) is highly recommended**, see [note!!!](#note)!
[ABSOLUTE](https://www.nature.com/articles/nbt.2203) is a famous
software developed by Broad Institute, however, the `RunAbsolute`
function is designed for computing one sample each time and set no
default values. **DoAbsolute** helps user set default parameters
according to [ABSOLUTE
documentation](http://software.broadinstitute.org/cancer/software/genepattern/modules/docs/ABSOLUTE),
provides a uniform interface to input data easily and runs **RunAbsolute**
parallelly.
More detail about how to analyze ABSOLUTE results please see [this link](http://software.broadinstitute.org/cancer/software/genepattern/analyzing-absolute-data).
## Installation
You can install the released version of DoAbsolute with:
``` r
# Option 1: GitHub
devtools::install_github("ShixiangWang/DoAbsolute")
# Option 2: r-universe
#
# Enable repository from shixiangwang
options(repos = c(
shixiangwang = 'https://shixiangwang.r-universe.dev',
CRAN = 'https://cloud.r-project.org'))
install.packages('DoAbsolute')
```
Install ABSOLUTE, the version provided by DoAbsolute is 1.0.6. You can
find available versions at .
Users of DoAbsolute all should accept LICENCE from Firehorse.
```r
install.packages("numDeriv")
path_to_file = system.file("extdata", "ABSOLUTE_1.0.6.tar.gz", package = "DoAbsolute", mustWork = T)
install.packages(path_to_file, repos = NULL, type="source")
```
> NOTE: the builtin ABSOLUTE package is modified for fitting current R version
> and reducing some errors (this may be described in NEWS.md).
> If you want to use the raw package without modification, you can find it
> [here](https://github.com/ShixiangWang/DoAbsolute/wiki/ABSOLUTE-raw-package).
> Remember the raw package (v1.0.6) is only working under R4.2.
## Example
This is a basic example which shows you how to run DoAbsolute using example data
from [ABSOLUTE documentation](http://software.broadinstitute.org/cancer/software/genepattern/modules/docs/ABSOLUTE).
Load package.
```{r, eval=FALSE}
library(DoAbsolute)
```
```{r example, eval=F}
example_path = system.file("extdata", package = "DoAbsolute", mustWork = T)
library(data.table)
# Load Test Data ----------------------------------------------------------
# segmentation file
seg_normal = file.path(example_path, "SNP6_blood_normal.seg.txt")
seg_solid = file.path(example_path, "SNP6_solid_tumor.seg.txt")
seg_metastatic = file.path(example_path, "SNP6_metastatic_tumor.seg.txt")
# MAF file
maf_solid = file.path(example_path, "solid_tumor.maf.txt")
maf_metastatic = file.path(example_path, "metastatic_tumor.maf.txt")
# read data
seg_normal = fread(seg_normal)
seg_solid = fread(seg_solid)
seg_metastatic = fread(seg_metastatic)
maf_solid = fread(maf_solid)
maf_metastatic = fread(maf_metastatic)
# merge data
Seg = Reduce(rbind, list(seg_normal, seg_solid, seg_metastatic))
Maf = Reduce(rbind, list(maf_solid, maf_metastatic))
Seg$Sample = substr(Seg$Sample, 1, 15)
Maf$Tumor_Sample_Barcode = substr(Maf$Tumor_Sample_Barcode, 1, 15)
# test function
DoAbsolute(Seg = Seg, Maf = Maf, platform = "SNP_6.0", copy.num.type = "total",
results.dir = "test", keepAllResult = TRUE, verbose = TRUE)
```
## NOTE!!!
Some inconsistent results have been reported in some issues (See discussion in and ), and it possibly relates to the parallel computation backend. **So, at default, run this tool with only 1 thread is highly recommended**!
## Citation
```
Wang, Shixiang, et al. "The predictive power of tumor mutational burden
in lung cancer immunotherapy response is influenced by patients' sex."
International journal of cancer (2019).
```
Reference:
* Carter, Scott L., et al. "Absolute quantification of somatic DNA alterations in human cancer." Nature biotechnology 30.5 (2012): 413.