README.md
In RIPAT: Retroviral Integration Pattern Analysis Tool (RIPAT)

RIPAT

Retroviral Integration Pattern Analysis Tool

This tool is developed for viral vector integration pattern analysis. Researchers who want to use this R package, need to input file generated by BLAST(NCBI) or BLAT(UCSC). If you have any question about this package, contact to author by this e-mail, mjbaek16@korea.ac.kr.

Install package We recommand the way using devtools package in R. But, you can download this package like zipped file from this repository. Plus, we wiil upload this package in Bioconductor repository. It's in progress.
Using devtools (Recommended)

devtools::install_github("bioinfo16/RIPAT")

Or, donwload it through the menu releases and enter the following command in the console. But, this way doesn't install package which is needed for running RIPAT.

R CMD INSTALL [PACKAGE_DOWNLOAD_PATH]

Package information If you want to use RIPAT, please install R (>=4.0) is recommanded. Plus, users can install these required packages (GeonomicRanges, IRanges, karyoploteR, regioneR) by this command below.

BiocManager::install('[PACKAGE_NAME]')

Requirements
R package list (version)
- biomaRt (>=2.38.0)
- GenomicRanges (>= 1.34.0)
- ggplot2 (>=3.1.0)
- grDevices (>=3.5.3)
- karyoploteR (>=1.6.3)
- openxlsx (>=4.1.4)
- plyr (>=1.8.4)
- RColorBrewer (>=1.1-2)
- regioneR (>=1.12.0)
- rtracklayer (>=1.42.2)
- stats (>=3.5.3)
- stringr (>=1.3.1)
- utils (>=3.5.3)
- Input format
- BLAST (Same with outfmt = 6 of command-line BLAST)
  
  Column_name | Contents --------------- | --------------- qseqid | query sequence id sseqid | subject sequence id pident | percentage of identical matches length | alignment length mismatch | number of mismatches gapopen | number of gap openings qstart | start of alignment in query qend | end of alignment in query sstart | start of alignment in subject send | end of alignment in subject evalue | expect value bitscore | bit score + BLAT *.psl format file
Session environment

R version 3.5.3 (2019-03-11)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=Korean_Korea.949  LC_CTYPE=Korean_Korea.949    LC_MONETARY=Korean_Korea.949
[4] LC_NUMERIC=C                 LC_TIME=Korean_Korea.949    

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] stringr_1.4.0        rtracklayer_1.42.2   RColorBrewer_1.1-2   plyr_1.8.5          
 [5] openxlsx_4.1.4       karyoploteR_1.8.8    regioneR_1.14.0      ggplot2_3.3.0       
 [9] GenomicRanges_1.34.0 GenomeInfoDb_1.18.2  IRanges_2.16.0       S4Vectors_0.20.1    
[13] BiocGenerics_0.28.0  biomaRt_2.38.0       RIPAT_0.99.8        

loaded via a namespace (and not attached):
 [1] ProtGenerics_1.14.0         bitops_1.0-6                matrixStats_0.55.0         
 [4] bit64_0.9-7                 progress_1.2.2              httr_1.4.1                 
 [7] tools_3.5.3                 backports_1.1.5             R6_2.4.1                   
[10] rpart_4.1-13                lazyeval_0.2.2              Hmisc_4.3-1                
[13] DBI_1.1.0                   colorspace_1.4-1            nnet_7.3-12                
[16] withr_2.1.2                 tidyselect_1.0.0            gridExtra_2.3              
[19] prettyunits_1.1.1           curl_4.3                    bit_1.1-15.2               
[22] compiler_3.5.3              Biobase_2.42.0              htmlTable_1.13.3           
[25] bezier_1.1.2                DelayedArray_0.8.0          scales_1.1.0               
[28] checkmate_2.0.0             digest_0.6.25               Rsamtools_1.34.1           
[31] foreign_0.8-71              XVector_0.22.0              base64enc_0.1-3            
[34] dichromat_2.0-0             pkgconfig_2.0.3             htmltools_0.4.0            
[37] ensembldb_2.6.8             BSgenome_1.50.0             htmlwidgets_1.5.1          
[40] rlang_0.4.5                 rstudioapi_0.11             RSQLite_2.2.0              
[43] BiocParallel_1.16.6         zip_2.0.4                   acepack_1.4.1              
[46] dplyr_0.8.4                 VariantAnnotation_1.28.13   RCurl_1.98-1.1             
[49] magrittr_1.5                GenomeInfoDbData_1.2.0      Formula_1.2-3              
[52] Matrix_1.2-15               Rcpp_1.0.3                  munsell_0.5.0              
[55] bamsignals_1.14.0           lifecycle_0.2.0             stringi_1.4.6              
[58] yaml_2.2.1                  SummarizedExperiment_1.12.0 zlibbioc_1.28.0            
[61] grid_3.5.3                  blob_1.2.1                  crayon_1.3.4               
[64] lattice_0.20-38             Biostrings_2.50.2           splines_3.5.3              
[67] GenomicFeatures_1.34.8      hms_0.5.3                   knitr_1.28                 
[70] pillar_1.4.3                XML_3.99-0.3                glue_1.3.1                 
[73] biovizBase_1.30.1           latticeExtra_0.6-28         data.table_1.12.8          
[76] vctrs_0.2.4                 gtable_0.3.0                purrr_0.3.3                
[79] assertthat_0.2.1            xfun_0.12                   AnnotationFilter_1.6.0     
[82] survival_3.1-8              tibble_3.0.1                GenomicAlignments_1.18.1   
[85] AnnotationDbi_1.44.0        memoise_1.1.0               cluster_2.0.7-1            
[88] ellipsis_0.3.0