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Copy file name to clipboardExpand all lines: src/REMsMoreThan2.Rmd
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@@ -3,24 +3,25 @@ Table \@ref(tab:associatedREMs) lists the interactions that overlap with at leas
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The second column provides the length of a REM, because the longer an interaction the higher the chance that several SNPs are overlapping.
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For example the interaction `r REMs$regionID[[1]]` of length `r REMs$length[[1]]`, which is associated to the gene `r REMs$gene[[1]]` overlaps with `r REMs$frequence[[1]]` (not necessarily unique) SNPs.
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For example the interaction `r REMs_table$regionID[[1]]` of length `r REMs_table$length[[1]]`, which is associated to the gene `r REMs_table$gene[[1]]` overlaps with `r REMs_table$frequence[[1]]` (not necessarily unique) SNPs.
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Similar as for the previous table, column *TFs* and *SNPs* help to differentiate if the same SNP has an impact on several TFs or the same TF is affected by multiple SNPs.
REMs$gene = gsub("_", "\\_", REMs$gene, fixed=TRUE) #necessary since escape must be false for linebreaking and the gene names can include _ which must be especially handled in latex (usually escape is taking care of this)
REMs_table$gene = gsub("_", "\\_", REMs_table$gene, fixed=TRUE) #necessary since escape must be false for linebreaking and the gene names can include _ which must be especially handled in latex (usually escape is taking care of this)
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knitr::kable(x = REMs, format = "latex",longtable = T, booktabs = T, col.names = c( "interaction ID", "length", "gene", "ensembl ID", "TFs", "SNPs", "frequency"), align = "llllllc", linesep = "", caption = "interactions overlapping at least 2 SNPs with a significant change in the binding affinity of a TF.", row.names = F, escape = F, label = "associatedREMs") %>%
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