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@@ -37,7 +37,7 @@ Note that this strategy is currently only available for `hg19`, `hg38`, `mm9` an
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Although CALDER was mainly tested on human and mouse dataset, it can be applied on dataset from other genomes. One additional information is required in such case: a `feature_track` that is presumably positively correlated with compartment score (thus higher values in A than in B compartment). This information will be used for correctly determing the `A/B` direction. Some suggested tracks are gene density, H3K27ac, H3K4me1, H3K4me2, H3K4me3, H3K36me3 (or negative transform of H3K9me3) signals. Note that this information will not alter the hierarchical compartment/TAD structure, and can come from any external study with matched genome.
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Although CALDER was mainly tested on human and mouse dataset, it can be applied on dataset from other genomes. One additional information is required in such case: a `feature_track` that is presumably positively correlated with compartment score (thus higher values in A than in B compartment). This information will be used for correctly determing the `A/B` direction. Some suggested tracks are gene density, H3K27ac, H3K4me1, H3K4me2, H3K4me3, H3K36me3 (or negative transform of H3K9me3) signals. Note that this information will not alter the hierarchical compartment/TAD structure, and can come from any external study with matched genome.
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+`feature_track` should be a data.frame or data.table having 4 columns (chr, start, end, score), and can be generated directly from conventional format such as bed or wig, such as the following example:
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Yuanlong LIU