microhomology analysis of SurVirus result
Erqiang Hu: Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University.
Shanye Yin: Albert Einstein College of Medicine
devtools::install_github("huerqiang/mhAnalysis")A significant proportion of human cancers result from the integration of viruses into the human genome. Therefore, investigating the mechanisms of viral integration is crucial for understanding the underlying mechanisms of many devastating diseases. Microhomology (MH) analysis at viral integration sites plays a critical role in the study of viral integration mechanisms. Previous research has shown a significant enrichment of microhomology (MH) between the human genome and the human papillomavirus (HPV) genome at integration breakpoints or nearby regions. To facilitate MH analysis, we have developed the mhAnalysis software package. The following sections provide an overview of the principles and usage of mhAnalysis.
SurVirus is an excellent software tool for analyzing viral integration sites with low false-positive and false-negative rates, providing researchers with reliable data. Therefore, mhAnalysis performs microhomology analysis by integrating with the results obtained from SurVirus.
In MH analysis, it is essential to obtain the integrated sequences, host sequences, and viral sequences at the integration sites. The retrieval of integrated sequences depends on the coordinates of the host and viral integration sites as well as their positive and negative strands. However, in some cases, SurVirus results may misidentify positive and negative strands. For example, if one integrated sequence has read1 recognizing the host’s positive strand and read2 recognizing the virus’s negative strand, SurVirus might incorrectly conclude that the host’s positive strand integrated with the virus’s negative strand when, in reality, the host’s positive strand integrated with the virus’s positive strand. To address this, we provide the add_strand() function to add accurate positive and negative strand information to the integrated sequences. This function first employs the internal get_r() function to identify which end each sequence belongs to and then selects single-end sequences that match both the virus and the host, using this information to determine the positive and negative strands for the virus and host.
When there is MH at the insertion sites, SurVirus results may suffer from misalignment issues. The misalignment length corresponds to the microhomology length at the insertion site. To rectify this and avoid complications in microhomology length statistics, we offer the get_real_loc() function, which identifies the genuine integration coordinates.
We provide the add_mh_flank() function to append MH length information within specified flanking regions to the SurVirus results. The process involves using the get_seq() function to add host sequence and virus sequence information within the defined flanking regions. These two sequences are combined to create the integrated sequence data. Subsequently, the virus sequence, host sequence, and integrated sequence are used as inputs to compute MH lengths using the get_mh function. The microhomology information is then incorporated into the SurVirus results. In conclusion, we have developed the mhAnalysis package to collaborate with the SurVirus software, particularly for MH analysis. Through mhAnalysis, we can accurately address MH issues at insertion sites, ensuring the accuracy and reliability of insertion site data. The introduction of this tool not only facilitates in-depth virology research but also provides powerful analytical tools in the field of bioinformatics to support the exploration of disease mechanisms and biological interactions.
devtools::install_github("huerqiang/mhAnalysis")data(BSgenomehpv16)
SurVirus_dir <- system.file(file.path("extdata", "survirus_result"),
package = "mhAnalysis")
bam_dir <- file.path(SurVirus_dir, "readsx")
result_t1 <- read.table(file.path(SurVirus_dir, "results.t1.txt"), sep = " ",
header = FALSE, fill = TRUE)
results <- read.table(file.path(SurVirus_dir, "results.txt"), sep = " ",
header = FALSE, fill = TRUE)
rownames(results) <- paste("ID", results[, 1], sep = "=")
results <- results[result_t1[, 1], ]
result_rel <- add_strand(results, bam_dir, result_t1)
result_rel <- get_real_loc(result_rel,
BSgenome_host = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,
BSgenome_virus=BSgenomehpv16)
result_rel <- get_seq(result_rel, len = 10,
BSgenome_host = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,
BSgenome_virus=BSgenomehpv16)
result_rel <- add_mh_flank(result_rel, len = 5)sessionInfo()
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