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)

• install R (>= 3.6)

• install Bioconductor (>=3.9)

run an R session and execute the following R code snippet

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
    
BiocManager::install("cpanse/NestLink", version = "3.9")  

or using docker

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 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.

Instructions to run on data and expected output is described in the package's vignettes.

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.

read the vignettes.

browseVignettes('NestLink')

• project p1875 at the Functional Genomics Center Zurich

• bioRxiv 2018/03/23/287813

• DOI:10.1038/s41592-019-0389-8