nf-core/circrna

You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See usage docs.

There are two rules for providing the phenotype CSV file. 1) The phenotype 'sample' column must match the sample sheets 'sample' column. 2) The response variable containing the phenotype of primary interest in the experiment must have the column name condition. All other columns included in the file are controlled for in the DESeq2 design.

| sample | condition | replicate |
|----------- |----------- |----------- |
| control_1 | ctr | 1 |
| control_2 | ctr | 2 |
| control_3 | ctr | 3 |
| treated_1 | trt | 1 |
| treated_2 | trt | 2 |
| treated_3 | trt | 3 |

The above phenotype file will identify differentially expressed circRNAs/mRNAs between control and treatment cells, whilst controlling for the effect of variation between replicates: ~ replicates + condition

Select one or a combination of circRNA quantification tools for the pipeline e.g:
--tool 'circexplorer2, ciriquant, find_circ'

N.B: Selecting more than one circRNA quantification tool will trigger the circRNA filtering parameter --tool_filter

The 'circrna_discovery' module is mandatory. After circRNA quantification, the user can select 'mirna_prediction', 'differential_expression' or both to deploy additional analyses e.g:
--module 'circrna_discovery, mirna_prediction, differential_expression'

Filter low confidence circRNAs by removing circRNAs with read counts below a specified value. To disable, set the value to 0 (default).

When multiple circRNA quantification tools have been provided to --tool, set a filtering method whereby circRNAs are output if they have been called by at least n quantification tools.

Setting --tool_filter to 0/1 is the same as taking the union, all circRNAs are included in the output.

Setting --tool_filter to 2 will output circRNAs that have been called by at least 2 quantification tools and so on.

Please note this is only reflected in the circRNA count matrix generated.

During annotation, if one of the start or end position of a circular candidate imperfectly overlaps an exon boundary, the script will consider positions within 'exon_boundary' (default 200bp) to be an exonic circRNA. If they fall outside of this range, the candidate is assumed to be an exonic-intronic circRNA, and the entire underlying sequence is taken for miRNA analysis, as opposed to just the exonic sequences for canonical exonic circRNAs.

This may either be in the form of FastQ or BAM files depending on the options available for that particular tool.

By using a reference genome build on iGenomes, the gtf, mature, species and index files (bar HISAT2 and segemehl) will be automatically downloaded for you.

See the nf-core website docs for more details.

If you use AWS iGenomes, this has already been set for you appropriately.

This parameter is mandatory if --genome is not specified.

Typically this will be the mature.fa file from miRBase. Can be given either as a plain text .fa file or a compressed .gz file.

Check the igenomes.config file for species configured to work with nf-core/circrna

HiSAT2 requires a huge amount of RAM to build a genome index for larger genomes, if including splice sites and exons e.g. the human genome might typically require 200GB. If you specify less than this threshold for the HISAT2_BUILD process then the splice sites and exons will be ignored, meaning that the process will require a lot less memory. If you are working with a small genome, set this parameter to a lower value to reduce the threshold for skipping this check. If using a larger genome, consider supplying more memory to the HISAT2_BUILD process.

Use this if your input FastQ files have already been trimmed outside of the workflow or if you're very confident that there is no adapter contamination in your data.

By default, trimmed FastQ files will not be saved to the results directory. Specify this flag (or set to true in your config file) to copy these files to the results directory when complete.

This enables the option Cutadapt --nextseq-trim=3'CUTOFF option via Trim Galore, which will set a quality cutoff (that is normally given with -q instead), but qualities of G bases are ignored. This trimming is in common for the NextSeq- and NovaSeq-platforms, where basecalls without any signal are called as high-quality G bases.

Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (~/.nextflow/config) then you don't need to specify this on the command line for every run.