About 20% of reads could be uniquely mapped to the genome for CLIP samples, while ~60% of reads could be uniquely aligned to the genome for RNAseq samples.
If a soft-clipped read contains the breakpoint(s) of an indel, we anticipate seeing a cluster of soft-clipped reads mapped to the same location around the breakpoints.
This pipeline discards reads that can only be mapped to the genome via soft clipping of their 5′ ends (i.e. the prefixes of these reads do not map to the genome).
After subtraction of adaptors, barcodes, multiple mapped reads and PCR duplicates, a total of 2 324 041 final tags from HLP1-CLIP were uniquely mapped to the Arabidopsis genome (TAIR10), whereas only 61 156 final tags from ΔRRM-CLIP were unique (Supplementary information, Table S1).
The deep sequencing reads were clipped of 3' adapters and mapped to the pig genome as previously described [ 35], except that no edits were allowed in the mapping.
Clipped reads were mapped to the hg19 genome and transcriptome using Bowtie2 version 2.0.6.
Clipped reads were mapped to the hg19 human genome using Tophat version 2.0.7 [ 19], and GMAP (GSNAP) version 2013-03-12 [ 18].
Clipped reads were mapped to the hg19 genome using Tophat version 2.0.7, and assembled with Cufflinks version 2.0.2, all with default parameter settings.
CLIP-Seq reads can be mapped to the genome or to the transcriptome in order to detect RNA binding activity.
After clipping and trimming, piRNAs from the testis pool were mapped to the tammar genome assembly Meug_2.0.
