customProDB
Bioc currentGenerate customized protein database from NGS data, with a focus on RNA-Seq data, for proteomics search
Release Lineage
Entered 2.13 · Oct 15, 2013
Current · Requires R 4.6
Description
Database search is the most widely used approach for peptide and protein identification in mass spectrometry-based proteomics studies. Our previous study showed that sample-specific protein databases derived from RNA-Seq data can better approximate the real protein pools in the samples and thus improve protein identification. More importantly, single nucleotide variations, short insertion and deletions and novel junctions identified from RNA-Seq data make protein database more complete and sample-specific. Here, we report an R package customProDB that enables the easy generation of customized databases from RNA-Seq data for proteomics search. This work bridges genomics and proteomics studies and facilitates cross-omics data integration.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
71 20 exported
Complexity
4.1 avg / 22 max
Call network
71 nodes / 68 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
5,562
Files
76
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
20
Internal functions
50
Testing & CI
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
30%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.0.1
System requirements
–
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
26
First release
2013-10-14
Latest release
2026-04-28
Avg cadence
181 days
Cold removal rate
–
Dep drift
7
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 90%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (1)
Bioconductor (1)
People
Xiaojing Wang
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("customProDB")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.