Custom reference data
The pipeline uses reference data at various stages. If you're using a common genome assembly, these resources are pre-built and can be easily downloaded using
refgenie pull, as described in the setup instructions. If the resources are not available, you'll have to build them. Read how to build
refgenie assets in the
refgenie docs. You may also learn about the current buildable assets to which
refgenie knows the recipe.
Use a custom
The pipeline will calculate the fraction of reads in genomic features using the
feat_annotation asset, but you can also specify this file yourself at the command line (
This annotation file is really just a modified
BED file, with the chromosomal coordinates and type of feature included. For example, the
hg38/feat_annotation asset looks like so:
chr1 70008 71585 3' UTR . + chr1 450702 450739 3' UTR . - chr1 685678 685715 3' UTR . - chr1 942695 943058 3' UTR . + chr1 942855 943058 3' UTR . + chr1 943252 943377 3' UTR . + chr1 943697 943808 3' UTR . + chr1 943907 944581 3' UTR . + chr1 944153 944574 3' UTR . + chr1 944202 944693 3' UTR . -
Just like a standard
BED file, the first three fields are:
1. chrom - the name of the chromosome
2. chromStart - the starting position of the feature
3. chromEnd - the ending position of the feature
Column four is the name column, in our case the name of our feature of interest. The fifth column is the score, which would determine how darkly an item would be displayed in a genome browser if you chose to set that or if the information in your file of interest has ascribed a score to the features. The final, sixth, column is the strand column.
After creating your
BED file, you can point the pipeline to it using the
--anno-name option followed with the path to your file. The pipeline will then use that file to determine the fractions of reads that cover those features. You could also tag this as an alternative
refgenie managed asset.