iMapSplice: Alleviating reference bias through personalized RNA-seq alignment.
Genomic variants in both coding and non-coding sequences can have functionally important and sometimes deleterious effects on exon splicing of gene transcripts. For transcriptome profiling using RNA-seq, the accurate alignment of reads across exon junctions is a critical step. Existing algorithms th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2018-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC6086400?pdf=render |
| _version_ | 1818550169316098048 |
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| author | Xinan Liu James N MacLeod Jinze Liu |
| author_facet | Xinan Liu James N MacLeod Jinze Liu |
| author_sort | Xinan Liu |
| collection | DOAJ |
| description | Genomic variants in both coding and non-coding sequences can have functionally important and sometimes deleterious effects on exon splicing of gene transcripts. For transcriptome profiling using RNA-seq, the accurate alignment of reads across exon junctions is a critical step. Existing algorithms that utilize a standard reference genome as a template sometimes have difficulty in mapping reads that carry genomic variants. These problems can lead to allelic ratio biases and the failure to detect splice variants created by splice site polymorphisms. To improve RNA-seq read alignment, we have developed a novel approach called iMapSplice that enables personalized mRNA transcriptome profiling. The algorithm makes use of personal genomic information and performs an unbiased alignment towards genome indices carrying both reference and alternative bases. Importantly, this breaks the dependency on reference genome splice site dinucleotide motifs and enables iMapSplice to discover personal splice junctions created through splice site polymorphisms. We report comparative analyses using a number of simulated and real datasets. Besides general improvements in read alignment and splice junction discovery, iMapSplice greatly alleviates allelic ratio biases and unravels many previously uncharacterized splice junctions created by splice site polymorphisms, with minimal overhead in computation time and storage. Software download URL: https://github.com/LiuBioinfo/iMapSplice. |
| first_indexed | 2024-12-12T08:42:52Z |
| format | Article |
| id | doaj.art-db4968b03826407cb8865bc719094dd2 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T08:42:52Z |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-db4968b03826407cb8865bc719094dd22022-12-22T00:30:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01138e020155410.1371/journal.pone.0201554iMapSplice: Alleviating reference bias through personalized RNA-seq alignment.Xinan LiuJames N MacLeodJinze LiuGenomic variants in both coding and non-coding sequences can have functionally important and sometimes deleterious effects on exon splicing of gene transcripts. For transcriptome profiling using RNA-seq, the accurate alignment of reads across exon junctions is a critical step. Existing algorithms that utilize a standard reference genome as a template sometimes have difficulty in mapping reads that carry genomic variants. These problems can lead to allelic ratio biases and the failure to detect splice variants created by splice site polymorphisms. To improve RNA-seq read alignment, we have developed a novel approach called iMapSplice that enables personalized mRNA transcriptome profiling. The algorithm makes use of personal genomic information and performs an unbiased alignment towards genome indices carrying both reference and alternative bases. Importantly, this breaks the dependency on reference genome splice site dinucleotide motifs and enables iMapSplice to discover personal splice junctions created through splice site polymorphisms. We report comparative analyses using a number of simulated and real datasets. Besides general improvements in read alignment and splice junction discovery, iMapSplice greatly alleviates allelic ratio biases and unravels many previously uncharacterized splice junctions created by splice site polymorphisms, with minimal overhead in computation time and storage. Software download URL: https://github.com/LiuBioinfo/iMapSplice.http://europepmc.org/articles/PMC6086400?pdf=render |
| spellingShingle | Xinan Liu James N MacLeod Jinze Liu iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. PLoS ONE |
| title | iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. |
| title_full | iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. |
| title_fullStr | iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. |
| title_full_unstemmed | iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. |
| title_short | iMapSplice: Alleviating reference bias through personalized RNA-seq alignment. |
| title_sort | imapsplice alleviating reference bias through personalized rna seq alignment |
| url | http://europepmc.org/articles/PMC6086400?pdf=render |
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