التفاصيل البيبلوغرافية
| العنوان: |
SNPlice: variants that modulate Intron retention from RNA-sequencing data. |
| المؤلفون: |
Mudvari, Prakriti1, Movassagh, Mercedeh1, Kowsari, Kamran1, Seyfi, Ali1, Kokkinaki, Maria, Edwards, Nathan J., Golestaneh, Nady, Horvath, Anelia1 horvatha@gwu.edu |
| المصدر: |
Bioinformatics. 4/15/2015, Vol. 31 Issue 8, p1191-1198. 8p. |
| مصطلحات موضوعية: |
*INTRONS, *SPLIT genes, *EXONS (Genetics), *RNA sequencing, *RNA analysis |
| مستخلص: |
Rationale: The growing recognition of the importance of splicing, together with rapidly accumulating RNA-sequencing data, demand robust high-throughput approaches, which efficiently analyze experimentally derived whole-transcriptome splice profiles. Results: We have developed a computational approach, called SNPlice, for identifying cis-acting, splice-modulating variants from RNA-seq datasets. SNPlice mines RNA-seq datasets to find reads that span single-nucleotide variant (SNV) loci and nearby splice junctions, assessing the cooccurrence of variants and molecules that remain unspliced at nearby exon--intron boundaries. Hence, SNPlice highlights variants preferentially occurring on intron-containing molecules, possibly resulting from altered splicing. To illustrate co-occurrence of variant nucleotide and exon-intron boundary, allele-specific sequencing was used. SNPlice results are generally consistent with splice-prediction tools, but also indicate splice-modulating elements missed by other algorithms. SNPlice can be applied to identify variants that correlate with unexpected splicing events, and to measure the splice-modulating potential of canonical splice-site SNVs. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
Full Text Finder