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https://github.com/cpanse/nestlink
Engineered Peptide Barcodes for In-Depth Analyses of Binding Protein Ensembles - replication code
https://github.com/cpanse/nestlink
bioconductor mass-spectrometry prediction retention-time rpackage sequencing simulation
Last synced: about 2 months ago
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Engineered Peptide Barcodes for In-Depth Analyses of Binding Protein Ensembles - replication code
- Host: GitHub
- URL: https://github.com/cpanse/nestlink
- Owner: cpanse
- License: gpl-2.0
- Created: 2015-10-28T11:06:52.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2022-05-10T08:12:46.000Z (almost 3 years ago)
- Last Synced: 2024-01-29T20:54:13.596Z (about 1 year ago)
- Topics: bioconductor, mass-spectrometry, prediction, retention-time, rpackage, sequencing, simulation
- Language: R
- Homepage: https://bioconductor.org/packages/NestLink
- Size: 38.6 MB
- Stars: 5
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# NestLink
Engineered Peptide Barcodes for In-Depth Analyses of Binding Protein Ensembles
available for download in the 'Devel' version of Bioconductor using `BiocManager::install("NestLink")`.
The package 'landing page' is available at https://bioconductor.org/packages/NestLink
(since 2019-01-14)
## 1. System requirements
### Software dependencies
- install R (>= 3.6)
- install Bioconductor (>=3.9)
## 2. Installation guide
run an R session and execute the following R code snippet
```{r}
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("cpanse/NestLink", version = "3.9")
```
or using [docker](https://cloud.docker.com/u/cpanse/repository/docker/cpanse/nestlink)
```
docker pull cpanse/nestlink \
&& docker run -a stdin -a stdout -i -t cpanse/nestlink /scratch/R-devel/bin/R
```
**Typical install time** -
based on the [Dockerfile](inst/scripts/Dockerfile) the install snippet above
took 19m46.464s on a linux server (RAID6, Intel(R) Xeon(R) CPU E5-2698 v3 @ 2.30GHz) and one hour on dockerhub.
As an alternative you can also consider the latest [release](https://github.com/cpanse/NestLink/releases).
### Versions the software has been tested on
|platform|NestLink version|platform version|R version|note|
| :------- |:---------------|:---------------| :-------|:------- |
|Linux | 0.99.51 | Debian 10 ([buster](https://www.debian.org/releases/testing/releasenotes)) | R 3.5.1, Bioconductor version 3.8| CP |
|Microsoft | 0.99.51 | Server 2012 R2 x64| R 3.5.0, Bioconductor version 3.7||
| macOS High| 0.99.51 | Sierra 10.13.4| R 3.4.2||
## 3. Demonstration / Documentation
Instructions to run on data and expected output is described in the package's
vignettes.
```{r}
browseVignettes('NestLink')
```
please study the vignettes in the following order:
0. Derive Peptide FlyCodes by Conducting Random Experiment
1. NGS filtering workflow to get high quality FlyCode and Nanobody sequences
2. FASTA p1875 db10 - ESP / SSRC prediction - Summary
3. Compare Predicted and Measured FlyCodes (F255744).
4. Control experiment to assess robustness of protein detection via flycodes
Expected run time for the vignette build is less than 5 minutes on a today's desktop computer.
## 4. Instructions for use
read the vignettes.
```{r}
browseVignettes('NestLink')
```
## References
- [project p1875 at the Functional Genomics Center Zurich](https://fgcz-bfabric.uzh.ch/bfabric/userlab/show-project.html?id=1875)
- [bioRxiv 2018/03/23/287813](https://www.biorxiv.org/content/early/2018/03/23/287813)
- [DOI:10.1038/s41592-019-0389-8](https://www.nature.com/articles/s41592-019-0389-8)