Journal article Open Access

Gene and pathway mutation scores for 5,805 primary tumors from TCGA

Kuijjer, Marieke Lydia


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        <foaf:name>Kuijjer, Marieke Lydia</foaf:name>
        <foaf:givenName>Marieke Lydia</foaf:givenName>
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    <dct:title>Gene and pathway mutation scores for 5,805 primary tumors from TCGA</dct:title>
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    <dcat:keyword>somatic mutations</dcat:keyword>
    <dcat:keyword>mutations</dcat:keyword>
    <dcat:keyword>SAMBAR</dcat:keyword>
    <dcat:keyword>de-sparsification</dcat:keyword>
    <dcat:keyword>cancer</dcat:keyword>
    <dcat:keyword>TCGA</dcat:keyword>
    <dcat:keyword>mutation data</dcat:keyword>
    <dcat:keyword>mutation scores</dcat:keyword>
    <dcat:keyword>pathway mutation scores</dcat:keyword>
    <dcat:keyword>biological pathways</dcat:keyword>
    <dcat:keyword>gene mutation scores</dcat:keyword>
    <dcat:keyword>subtypes</dcat:keyword>
    <dcat:keyword>cancer subtypes</dcat:keyword>
    <dcat:keyword>pan-cancer</dcat:keyword>
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    <dct:description>&lt;p&gt;This dataset contains gene and pathway mutation scores for 5,805 primary tumors from 23 different cancer types from The Cancer Genome Atlas (TCGA).&lt;br&gt; &lt;br&gt; Gene mutation scores of 2,219 cancer-associated genes were calculated by normalizing the number of non-silent mutations in a gene (obtained from .maf files from TCGA) by the gene&amp;#39;s length. We used SAMBAR (Subtyping Agglomerated Mutations By Annotation Relations) to calculate pathway mutation scores. In short, SAMBAR takes the sum of mutation scores of all genes belonging to a biological pathway and then corrects these scores for the pathway&amp;#39;s gene set size and the number of times a gene is represented in the complete set of pathways. Please see &lt;a href="https://www.nature.com/articles/s41416-018-0109-7"&gt;our publication&lt;/a&gt; in the &lt;em&gt;British Journal of Cancer&lt;/em&gt; for methodological details.&lt;/p&gt; &lt;p&gt;In the RData file &amp;quot;TCGA_SAMBAR.RData&amp;quot;, we share the following objects:&lt;/p&gt; &lt;p&gt;- &lt;strong&gt;gene_scores&lt;/strong&gt;: a 2219 by 5805 numeric matrix including gene (rows) mutation scores for each sample (columns).&lt;/p&gt; &lt;p&gt;- &lt;strong&gt;pathway_scores&lt;/strong&gt;: a 1066 by 5805 numeric matrix including pathway (rows) mutation scores for each sample (columns).&lt;br&gt; &lt;br&gt; The file &amp;quot;sample_tumor_annotation.RData&amp;quot; contains the object:&lt;br&gt; &lt;br&gt; - &lt;strong&gt;sample_annotation&lt;/strong&gt;: a 5805 by 2 character matrix including sample names (first column) and the tumor type the sample belongs to (&lt;a href="https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations"&gt;TCGA Study Abbreviations&lt;/a&gt;).&lt;/p&gt;</dct:description>
    <dct:description>This work was funded through a grant from the NVIDIA foundation (grant no. 2014-133322 (3953)). This work was additionally supported by a Postdoctoral Fellowship Program from the Charles A. King Trust Fund, Sara Elizabeth O'Brien Trust, Bank of America, N.A., co-Trustees.</dct:description>
    <dct:description>{"references": ["Kuijjer, Marieke Lydia, et al. Br J Cancer. 2018 May;118(11):1492-1501"]}</dct:description>
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