Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/Roleren/coverageSim
https://github.com/Roleren/coverageSim
Last synced: 3 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/Roleren/coverageSim
- Owner: Roleren
- License: mit
- Created: 2023-03-29T21:44:43.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2023-08-08T11:43:19.000Z (about 1 year ago)
- Last Synced: 2024-07-01T18:35:01.815Z (4 months ago)
- Language: R
- Size: 150 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-riboseq - Code
README
# coverageSim
### Simulating Ribosome profiling data for tool validation
![](inst/images/coverageSim_overview.png)## How to install
```r
if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools")
devtools::install_github("Roleren/coverageSim")
```## Simple example
Lets make a genome with 6 genes, each being coding (they have a CDS) and
having 1 translated uORF:```r
library(coverageSim)
library(ORFik)
## Simple example
# 6 genes on 6 chromosomes (1 active uORF each)
simGenome6 <- simGenome(n = 6, max_uorfs = 1)
# Simulate Ribo-seq only
gene_count_table <-simCountTables(loadRegion(simGenome6["txdb"], "cds"),
libtypes = "RFP", print_statistics = FALSE)
region_count_table <- simCountTablesRegions(gene_count_table,
regionsToSample = c("leader", "cds", "trailer"))
df <- simNGScoverage(simGenome6, region_count_table)
```The ORFik experiment object (df), now contains all linkers to resulting files.
## Convert to other track formats
```r
# Convert to bigwig
ORFik::convert_to_bigWig(df)```
ORFik supports multiple other formats to convert to, also coverageSim internally has
a option to simulate bam files from the ofst track output files.## Relevant paths for other programs
```r
# Transcript annotation (.gtf)
gtf_path <- ORFik:::getGtfPathFromTxdb(loadTxdb(df))
# Genome sequences (.fasta)
fasta_genome_path <- df@fafile
# NGS track files (.bigwig, pairwise for forward and reverse strands)
bigwig_paths <- filepath(df, "bigwig")
```## Export to IGV
- Open IGV,
- Press "Genomes" tab (top left), "Create .genome file"
- Unique Identifier: "Sim genome", Descriptive name: "Sim genome",
- FASTA file: input fasta_genome_path above
- Gene file: input gtf_path above
- Press OKNow load bigwig files by:
- Press "File" (top left), "Load from File"
- load all paths from bigwig_paths aboveYou now have genome, gtf and tracks loaded in IGV