Literature DB >> 27049861

Correction: Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools.

Omar Soukarieh, Pascaline Gaildrat, Mohamad Hamieh, Aurélie Drouet, Stéphanie Baert-Desurmont, Thierry Frébourg, Mario Tosi, Alexandra Martins.   

Abstract

Entities:  

Year:  2016        PMID: 27049861      PMCID: PMC4822950          DOI: 10.1371/journal.pgen.1005971

Source DB:  PubMed          Journal:  PLoS Genet        ISSN: 1553-7390            Impact factor:   5.917


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There is an error in Fig 4. The symbol for correlation coefficient "ρ" should be replaced with "r", to match the description in the main text and Figure legend. Please see the correct Fig 4 here.
Fig 4

Correlation analysis between exon 10 inclusion levels and results obtained from new ESR-dedicated bioinformatics tools.

(A), (B) and (C) refer to results obtained with ΔtESRseq-, ΔHZEI- and ΔΨ-based bioinformatics approaches, respectively, as described under Materials and Methods. Only MLH1 exon 10 variants located outside the sequences that define the reference splice sites were retained for this analysis as already mentioned in Fig 3. The precise correspondence between each Δ value (ΔtESRseq, ΔHZEI or ΔΨ), the level of exon inclusion observed in the pSPL3m-M1e10 minigene assay, and the identity of the corresponding MLH1 exon 10 variant, is indicated on S1 Table. Correlation coefficients (r) and p-values were determined by performing a Pearson correlation analysis, as described under Materials and Methods.

Correlation analysis between exon 10 inclusion levels and results obtained from new ESR-dedicated bioinformatics tools.

(A), (B) and (C) refer to results obtained with ΔtESRseq-, ΔHZEI- and ΔΨ-based bioinformatics approaches, respectively, as described under Materials and Methods. Only MLH1 exon 10 variants located outside the sequences that define the reference splice sites were retained for this analysis as already mentioned in Fig 3. The precise correspondence between each Δ value (ΔtESRseq, ΔHZEI or ΔΨ), the level of exon inclusion observed in the pSPL3m-M1e10 minigene assay, and the identity of the corresponding MLH1 exon 10 variant, is indicated on S1 Table. Correlation coefficients (r) and p-values were determined by performing a Pearson correlation analysis, as described under Materials and Methods. There is a typographical error in the last sentence of the paragraph following Fig 4 (Results section): ‘ΔΔHZEI’ should be replaced with ‘ΔHZEI’. The correct sentence is: “Moreover, given their lack of comprehensiveness and global quantitation, the performance of these two in silico tools could not be statistically analyzed, nor properly compared to that of ΔtESRseq, ΔHZEI, ΔΨ or EX-SKIP.”
  1 in total

1.  Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools.

Authors:  Omar Soukarieh; Pascaline Gaildrat; Mohamad Hamieh; Aurélie Drouet; Stéphanie Baert-Desurmont; Thierry Frébourg; Mario Tosi; Alexandra Martins
Journal:  PLoS Genet       Date:  2016-01-13       Impact factor: 5.917

  1 in total
  2 in total

1.  Exonic CLDN16 mutations associated with familial hypomagnesemia with hypercalciuria and nephrocalcinosis can induce deleterious mRNA alterations.

Authors:  Ana Perdomo-Ramirez; Marian de Armas-Ortiz; Elena Ramos-Trujillo; Lorena Suarez-Artiles; Felix Claverie-Martin
Journal:  BMC Med Genet       Date:  2019-01-08       Impact factor: 2.103

2.  Splicing dysregulation contributes to the pathogenicity of several F9 exonic point variants.

Authors:  Upendra K Katneni; Aaron Liss; David Holcomb; Nobuko H Katagiri; Ryan Hunt; Haim Bar; Amra Ismail; Anton A Komar; Chava Kimchi-Sarfaty
Journal:  Mol Genet Genomic Med       Date:  2019-06-30       Impact factor: 2.183

  2 in total

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