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README.md

@@ -37,7 +37,7 @@ Note that this strategy is currently only available for `hg19`, `hg38`, `mm9` an
 Although CALDER was mainly tested on human and mouse dataset, it can be applied to dataset from other genomes. One additional information is required in such case: a `feature_track` 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.
 Although CALDER was mainly tested on human and mouse dataset, it can be applied to dataset from other genomes. One additional information is required in such case: a `feature_track` 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:
+`feature_track` should be a data.frame or data.table of 4 columns (chr, start, end, score), and can be generated directly from conventional format such as bed or wig, see the following example:
 
 
 ```
 ```
 library(rtracklayer)
 library(rtracklayer)