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changes for #9943 on frontend #4576

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changes for #9943 on frontend #4576

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2 changes: 1 addition & 1 deletion src/pages/resultsView/enrichments/AlterationEnrichmentsTable.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -189,7 +189,7 @@ export default class AlterationEnrichmentTable extends React.Component<
Derived from{' '}
{_.values(this.props.data[0].groupsSet).length > 2
? 'Chi-squared test'
: 'one-sided Fisher Exact test'}
: 'two-sided Fisher Exact test'}
</span>
) : (
undefined
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2 changes: 1 addition & 1 deletion src/pages/resultsView/mutualExclusivity/MutualExclusivityTable.tsx
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Expand Up @@ -181,7 +181,7 @@ export default class MutualExclusivityTable extends React.Component<
render: (d: MutualExclusivity) => (
<span>{formatPValue(d.pValue)}</span>
),
tooltip: <span>Derived from one-sided Fisher Exact Test</span>,
tooltip: <span>Derived from two-sided Fisher Exact Test</span>,
sortBy: (d: MutualExclusivity) => d.pValue,
download: (d: MutualExclusivity) => formatPValue(d.pValue),
};
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6 changes: 6 additions & 0 deletions src/shared/lib/FisherExactTestCalculator.ts
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@@ -1,3 +1,5 @@
// Calculates the probability of observing the observed counts (a,b,c,d) in a 2x2 contingency table
// given the total count (n) and the factorial of the counts (logFactorial).
function getProbability(
a: number,
b: number,
Expand All @@ -19,6 +21,7 @@ function getProbability(
return Math.exp(p);
}

// Cumulative p-value for a 2x2 contingency table using Fisher's exact test
export function getCumulativePValue(
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I think in MutualExclusivityTable, we are using getCumulativePValue function in FisherExactTestCalculator.ts to calculate one-sided Fisher's exact test right now. So we might need to implement a new method for this table to calculate two-sided Fisher's exact test. You can reference the backend implementation: https://github.com/cBioPortal/cbioportal/blob/master/core/src/main/java/org/mskcc/cbio/portal/stats/FisherExact.java#L240

a: number,
b: number,
Expand All @@ -35,14 +38,17 @@ export function getCumulativePValue(
logFactorial[j] = logFactorial[j - 1] + Math.log(j);
}

// probability for the given contingency table
p += getProbability(a, b, c, d, logFactorial);
// cumulative p-value for all tables with greater proportion of observations in 1st row and 1st column
if (a * d >= b * c) {
min = c < b ? c : b;
for (i = 0; i < min; i++) {
p += getProbability(++a, --b, --c, ++d, logFactorial);
}
}

// cumulative p-value for all tables with greater proportion of observations in 2nd row and 2nd column
if (a * d < b * c) {
min = a < d ? a : d;
for (i = 0; i < min; i++) {
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