The estimated frequencies of bases at two 5′ to the mutated site for each cancer type.

<p>The bar heights show the estimated frequency for bases A, C, G and T at the −2 position (two 5′ to the mutated site). The error bars show bootstrapped standard errors. (A, B, C, D, E) The intensities of signature 13 (APOBEC signature), signature 1 (the first Pol <i>ϵ</i> signature), signature 8 (the second Pol <i>ϵ</i> signature), signature 10 (ultraviolet signature) and signature 11, respectively, at the −2 position.</p

An overview of the generative model of somatic mutations proposed in this paper.

<p>Suppose there are three types of mutation sources (mutation signatures) such as ultraviolet, tobacco smoking chemicals and transcription coupled repairs. Each cancer genome has ratios showing which types of mutation sources are contributing to its mutations (membership parameters). The generative model of the pattern of each mutation is: first, one of the mutation signatures is chosen according to the membership parameter. Second, each mutation feature such as substitution patterns and flanking bases is generated by the corresponding multinomial distributions for the selected mutation signature.</p

The mutation signatures for the UCUT data, and the results of down-sampling experiments.

<p>3,072 elements in the full model mutation signatures were shown divided by 6 substitution patterns and strand directions. (A, B) APOBEC and AA signature for the independent model. (C, D) APOBEC and AA signature for the full model. (E, F) APOBEC and AA signature stability (the mean cosine similarity for each down-sampling ratio).</p

The summary of mutation signatures across 30 cancer types [8] obtained using the proposed method.

<p>Here, the substitution patterns and two 5′ and 3′ bases from the mutated sites are taken into account as mutation features. First, mutation signatures were estimated separately in each cancer type, and then similar signatures were merged (see text).</p

The summary of membership of each mutation signature across 30 cancer types obtained using the proposed method.

<p>The summary of membership of each mutation signature across 30 cancer types obtained using the proposed method.</p

Examples of visualizations and parameter values for the mutation signatures of the unconstrained (full) model and our independent model, where substitution patterns, two 5′ and 3′ bases and transcription strand direction are considered as mutation features.

<p>(A) The barplots are divided by 6 substitution patterns and transcription strand direction. In each division, 256 bars show joint probabilities of up to two base 5′ and 3′ bases (ApApNpApA, ApApNpApC, ApApNpApG, ApApNpApT, ⋯, TpTpNpTpT). (B, C) An example mutation signature representation and parameter values from our independent model, where mutation features (substitution patterns, two 5′ and 3′ bases and strand direction) are assumed to be independent (<i>L</i> = 6, <i><b>M</b></i> = (6, 4, 4, 4, 4, 2)). In the bottom five rectangles, the width of each box represents the frequencies of bases (A, C, G and T) at the substitution and flanking site. To highlight the most informative flanking sites, the heights of flanking site boxes are scaled by <math><mrow><mn>1</mn><mo>+</mo><mn>0</mn><mo>.</mo><mn>5</mn><mo>×</mo><mo>log</mo><msub><mo>∑</mo><mrow><mi>n</mi><mo>=</mo><mi>A</mi><mo>,</mo><mi>C</mi><mo>,</mo><mi>G</mi><mo>,</mo><mi>T</mi></mrow></msub><msubsup><mi>f</mi><mi>n</mi><mn>2</mn></msubsup></mrow></math>, where <i>f</i>_<i>n</i> is the parameter for each base, which can be interpreted as 1 − 0.5 × Rényi entropy [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005657#pgen.1005657.ref017" target="_blank">17</a>]. This is analogous to the information content scaling used in sequencing logos. In the top rectangle, the height of each box represents the conditional frequencies of mutated bases for each original base (C and T). In the upper right, the height of the + box represents the frequencies of mutations in the coding strand (the plus strand, the sense strand or the untranscribed strand in other words) whose nucleotide sequences directly corresponds to mRNA, whereas the height of − box represents those in the template strand (the minus strand, the antisense strand, the transcribed strand or the noncoding strand in other words) whose sequences are copied during the synthesis of mRNA.</p

Relationships among mutation signature model, topic models, and population structure models.

<p>Relationships among mutation signature model, topic models, and population structure models.</p

Hypermethylation status and clinical outcome in patients with juvenile myelomonocytic leukemia (JMML).

<p>(A) Kaplan–Meier curves represent the probability of transplantation-free survival (TFS) in the 92 patients with JMML. TFS was defined as the probability of being alive and transplantation free. Both death and transplantation were considered events. The probability of 5-year TFS in the aberrant methylation score (AMS) 0 cohort (solid line) was significantly higher than that in the AMS 1–2 (long dashed line) and AMS 3–4 cohorts (dashed line), p < 0.001. (B) Kaplan–Meier curves represent the probability of overall survival (OS) in the 92 patients with JMML. Death was considered an event. The probability of OS in both the AMS 0 (solid line) and 1–2 cohorts (long dashed line) was significantly higher than that in the AMS 3–4 cohort (dashed line), p < 0.001.</p

Profile of genetic mutations and aberrant methylation.

<p>(A) Mutation status of RAS pathway genes and secondary genes (<i>SETBP1</i> and <i>JAK3</i>) identified as gene targets. Aberrant methylation scores (AMS) in a cohort of 92 patients with juvenile myelomonocytic leukemia are summarized. A rhombus denotes a patient with Noonan syndrome-associated myeloproliferative disorder. (B) Mutations in <i>SETBP1</i> and <i>JAK3</i> were associated with a higher AMS. The mean AMS of patients with <i>SETBP1</i> and/or <i>JAK3</i> mutations was higher than that of patients without secondary mutations (p = 0.03).</p

Summary of DNA methylation in candidate genes.

<p>(A) The dot plot represents the frequencies of methylated CpG sites for each candidate gene in the 92 patients with juvenile myelomonocytic leukemia. Aberrant hypermethylation was defined as >3 standard deviations above the mean methylation level of the healthy control population. The threshold values of each gene are shown as red broken lines. (B) Kaplan–Meier plots of the patient groups, defined by aberrant methylation of the indicated genes, are shown for <i>BMP4</i>, <i>CALCA</i>, <i>CDKN2A</i>, <i>CDKN2B</i>, <i>H19</i>, and <i>RARB</i>.</p