2016
DOI: 10.1371/journal.pone.0160519
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Lollipops in the Clinic: Information Dense Mutation Plots for Precision Medicine

Abstract: IntroductionConcise visualization is critical to present large amounts of information in a minimal space that can be interpreted quickly. Clinical applications in precision medicine present an important use case due to the time dependent nature of the interpretations, although visualization is increasingly necessary across the life sciences. In this paper we describe the Lollipops software for the presentation of panel or exome sequencing results. Source code and binaries are freely available at https://github… Show more

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Cited by 114 publications
(104 citation statements)
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“…Furthermore, mapping the mutations and its statistics on a linear gene product (proteins of interest) was done with a ‘lollipop’ mutation diagram generator (49). Based on the knowledge from the human MMR-D counterpart and general involvement in tumorigenesis, the genes for further analysis were chosen with high probability to mutate.…”
Section: Methodsmentioning
confidence: 99%
“…Furthermore, mapping the mutations and its statistics on a linear gene product (proteins of interest) was done with a ‘lollipop’ mutation diagram generator (49). Based on the knowledge from the human MMR-D counterpart and general involvement in tumorigenesis, the genes for further analysis were chosen with high probability to mutate.…”
Section: Methodsmentioning
confidence: 99%
“…Here, we use lollipops-v.1.3.1 (Jay and Brouwer 2016) to plot the distribution of the 606 qualified pathogenic variants across the linear gene structure of the 11 epilepsy genes (Methods; Fig. 2).…”
Section: Identifying Missense-intolerant Subregions Of Genesmentioning
confidence: 99%
“…Variants in each sample were further filtered for high genotype quality (≥20), and annotated according to Human Genome Variation Society Gene scheme structure was generated by using Lollipops (Jay & Brouwer, 2016). RNA-seq data analysis was performed by using kallisto and DEseq2 (Bray, Pimentel, Melsted, & Pachter, 2016).…”
Section: Bioinformaticsmentioning
confidence: 99%