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        <title>TIMER2.0 for analysis of tumor-infiltrating immune cells</title>
        <author>Taiwen Li</author>
        <author>Jingxin Fu</author>
        <author>Zexian Zeng</author>
        <author>David Cohen</author>
        <author>Jing Li</author>
        <author>Qianming Chen</author>
        <author>Bo Li</author>
        <author>X. Shirley Liu</author>
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          <title>TIMER2.0 for analysis of tumor-infiltrating immune cells</title>
          <date>2020</date>
          <publisher>Nucleic Acids Research</publisher>
          <idno type="DOI">10.1093/nar/gkaa407</idno>
          
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      <span xml:id="t0" type="object_of_study" ana="#object_of_study" resp="#paper">
        <label>immune cell composition of tumours - a quantity that is inferred from bulk transcriptome rather than counted, by six different algorithms</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t1" type="research_question" ana="#research_question" resp="#paper">
        <label>how to make immune-infiltration estimates from public tumour data usable without committing to any one inference algorithm</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t2" type="contribution" ana="#contribution" resp="#paper">
        <label>a web platform that runs six estimation algorithms over uniformly pre-processed TCGA data and shows their outputs side by side</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t3" type="claim_type" ana="#claim_type" resp="#paper">
        <label>method</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <span xml:id="t4" type="phenomenon" ana="#phenomenon" resp="#paper">
        <label>tumour immune infiltration, whose direct measurement is limited enough that the field works from computational inference instead</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t5" type="method" ana="#method" resp="#paper">
        <label>system-or-tool-building</label>
        <term>system-or-tool-building</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t6" type="mechanisms" ana="#mechanisms[0]" resp="#tagger" cert="0.95">
        <label>gene-signature methods score cell-type-specific gene sets INDEPENDENTLY per cell type; deconvolution methods model the tissue&#x27;s expression as a WEIGHTED SUM of the component cells&#x27; profiles. Two different mathematical objects behind one output name</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t7" type="limitations" ana="#limitations[0]" resp="#tagger" cert="0.95">
        <label>THE QUANTITY IS NOT MEASURED. `Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition` - and the transcriptome `does not immediately indicate` it</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t8" type="limitations" ana="#limitations[1]" resp="#tagger" cert="0.95">
        <label>SIX ALGORITHMS, ONE OUTPUT NAME, AND ONLY TWO PRODUCE A QUANTITY ON A MEANINGFUL SCALE: `EPIC and quanTIseq have the advantage of directly generating scores interpreted as cell fractions`. The other four produce enrichment scores displayed beside them</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t9" type="limitations" ana="#limitations[2]" resp="#tagger" cert="0.95">
        <label>each algorithm is named with its own failure: TIMER handles tissue specificity but covers only six cell types, xCell covers more but MAY FAIL TO DETECT SIGNALS FROM HOMOGENEOUS SAMPLES</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t10" type="limitations" ana="#limitations[3]" resp="#tagger" cert="0.95">
        <label>the justification for running all six is a HOPE, in the authors&#x27; own word: `We hope that evaluating estimations from multiple algorithms might help the user gain more comprehensive and robust results`</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t11" type="limitations" ana="#limitations[4]" resp="#tagger" cert="0.95">
        <label>and the cross-species use is caveated where it is offered: mouse estimations `should be interpreted with caution since human and the mouse tumors may have different immune properties`</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t12" type="controls" ana="#controls[0]" resp="#tagger" cert="0.95">
        <label>all TCGA samples are pre-processed UNIFORMLY before the six algorithms run, so the estimates differ by algorithm and not by pipeline</label>
        <note>eliminates: disagreement between algorithms that is really disagreement between normalisations - which is the only way the side-by-side display could mean anything · outcome: held</note>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t13" type="controls" ana="#controls[1]" resp="#tagger" cert="0.95">
        <label>whether the six estimates are on the same scale</label>
        <note>eliminates: nothing - EPIC and quanTIseq generate cell fractions and the rest do not, and the platform shows all six together without reconciling them · outcome: failed</note>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t14" type="controls" ana="#controls[2]" resp="#tagger" cert="0.95">
        <label>whether running six algorithms actually yields more robust results</label>
        <note>eliminates: nothing that is demonstrated here - the claim is &#x27;We hope ... might help&#x27;, with no comparison against single-algorithm use reported · outcome: absent-declared-unreported</note>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t15" type="concepts" ana="#concepts[0]" resp="#paper" cert="0.95">
        <label>deconvolution</label>
        <term>deconvolution</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <span xml:id="t16" type="concepts" ana="#concepts[1]" resp="#paper" cert="0.95">
        <label>cell fractions</label>
        <term>cell fractions</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <span xml:id="t17" type="concepts" ana="#concepts[2]" resp="#paper" cert="0.95">
        <label>xCell</label>
        <term>xCell</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <span xml:id="t18" type="concepts" ana="#concepts[3]" resp="#paper" cert="0.95">
        <label>TIMER</label>
        <term>TIMER</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <span xml:id="t19" type="senses" ana="#senses[0]" resp="#tagger" cert="0.95">
        <label>immune infiltration level - AS DELIVERED BY THIS PLATFORM, SIX DIFFERENT QUANTITIES UNDER ONE HEADING. Two are cell fractions, four are enrichment scores, and the platform&#x27;s design is to show them together rather than to reconcile them. THE NAME IS THE ONLY THING THE SIX SHARE</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t20" type="senses" ana="#senses[1]" resp="#tagger" cert="0.95">
        <label>estimation, AS OPPOSED TO MEASUREMENT - the paper&#x27;s own framing throughout, and it is honest: direct measurement is limited, so the field infers. Every number this server is cited for is downstream of that sentence</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t21" type="senses" ana="#senses[2]" resp="#tagger" cert="0.95">
        <label>robustness, AS THIS PLATFORM OPERATIONALISES IT: agreement across six algorithms, displayed for the user to judge. Not a statistic, not a test - A LAYOUT. And the authors say they HOPE it helps</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t22" type="claim_relations" ana="#claim_relations[0]" resp="#tagger" cert="0.95">
        <label>critiques → reliance on any single immune-infiltration algorithm, since the two families have variable performance advantages across cell types and tumours</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t23" type="claim_relations" ana="#claim_relations[1]" resp="#tagger" cert="0.95">
        <label>extends → the original TIMER web server, which used one algorithm where this uses six</label>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t24" type="content_tags" ana="#content_tags.findings[0]" resp="#tagger" cert="0.95">
        <label>THE QUANTITY IS INFERRED, NOT MEASURED: due to the limitations of direct measurement methods, immune cell composition is computed from bulk transcriptome</label>
        <term>THE QUANTITY IS INFERRED, NOT MEASURED: due to the limitations of direct measurement methods, immune cell composition is computed from bulk transcriptome</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t25" type="content_tags" ana="#content_tags.findings[1]" resp="#tagger" cert="0.95">
        <label>EPIC and quanTIseq directly generate scores interpreted as cell fractions</label>
        <term>EPIC and quanTIseq directly generate scores interpreted as cell fractions</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t26" type="content_tags" ana="#content_tags.findings[2]" resp="#tagger" cert="0.95">
        <label>each algorithm carries its own failure mode - TIMER covers only six cell types, xCell may fail to detect signals from homogeneous samples</label>
        <term>each algorithm carries its own failure mode - TIMER covers only six cell types, xCell may fail to detect signals from homogeneous samples</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t27" type="content_tags" ana="#content_tags.findings[3]" resp="#tagger" cert="0.95">
        <label>the reason for running all six is stated as a HOPE: `We hope that evaluating estimations from multiple algorithms might help the user gain more comprehensive and robust results`</label>
        <term>the reason for running all six is stated as a HOPE: `We hope that evaluating estimations from multiple algorithms might help the user gain more comprehensive and robust results`</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t28" type="content_tags" ana="#content_tags.findings[4]" resp="#tagger" cert="0.95">
        <label>mouse estimations SHOULD BE INTERPRETED WITH CAUTION because human and mouse tumours may have different immune properties - the caveat is placed where the feature is offered</label>
        <term>mouse estimations SHOULD BE INTERPRETED WITH CAUTION because human and mouse tumours may have different immune properties - the caveat is placed where the feature is offered</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t29" type="content_tags" ana="#content_tags.definitions[0]" resp="#tagger" cert="0.95">
        <label>methods that model the gene expression of a tissue sample as the weighted sum of the expression profiles from the cells in the population mix</label>
        <term>Deconvolution</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t30" type="content_tags" ana="#content_tags.statistics[0]" resp="#tagger" cert="0.95">
        <label>deconvolution</label>
        <term>deconvolution</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
      </span>
      <span xml:id="t31" type="content_tags" ana="#content_tags.variables[0]" resp="#tagger" cert="0.95">
        <label>tissue specificity</label>
        <term>tissue specificity</term>
        <note type="quotation-withheld">Quotation withheld because this record is not cleared for redistribution.</note>
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      <p><note type="rights">The full text of this article is not redistributable, so it is
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      grounding status remain. The article itself is at https://doi.org/10.1093/nar/gkaa407.</note></p>
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