nf-core/cageseq
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CAGE-sequencing analysis pipeline with trimming, alignment and counting of CAGE tags.

cagecage-seqcageseq-datagene-expressionrna

This is the development version of the pipeline.

This pipeline uses DSL1. It will not work with Nextflow versions after 22.10.6. Learn more.

Launch development version https://github.com/nf-core/cageseq

Introduction

This document describes the output produced by the pipeline. The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.

Reads can be mapped using STAR (to take splacing into account and to obtain bigWig files with raw 5’-coverage; STAR is used by default) or bowtie2 (see the --bowtie2 option below). The pipeline can generate a genome index on the fly if provided with a FASTA file. For genome generation with STAR, user can also provide a GTF file. Apart from the CAGEexp object and raw 5’-coverage bigWig files (if reads were mapped with STAR), the pipeline produces BAM files with filtered alignments that could be used for a separate analysis and a detailed MultiQC report.

Output

Content of the results folder

Below is the complete tree of the results run on 2 samples with the STAR option.

├── bigwig
│   ├── <sample_name_1>.Signal.Unique.str1.out.wig.bw
│   ├── <sample_name_1>.Signal.Unique.str2.out.wig.bw
│   ├── <sample_name_2>.Signal.Unique.str1.out.wig.bw
│   ├── <sample_name_2>.Signal.Unique.str2.out.wig.bw
│   └── versions.yml
├── cager
│   ├── cager_report.html
│   ├── intermediate_cagerobj
│   │   ├── annotated_cagexp.rds
│   │   ├── initial_cagexp.rds
│   │   ├── nonTSS_enhancers.rds
│   │   ├── normalized_clustered_cagexp.rds
│   │   └── supported_enhancers.rds
│   ├── plots
│   │   ├── chipseeker_enhancer_annotation_plot.pdf
│   │   ├── chipseeker_enhancer_annotation_plot.rds
│   │   ├── chipseeker_tagCluster_annotation_plot.pdf
│   │   ├── chipseeker_tagCluster_annotation_plot.rds
│   │   ├── consensus_clusters_pca_plot.pdf
│   │   ├── consensus_clusters_pca_plot.rds
│   │   ├── consensus_counts_plot.pdf
│   │   ├── consensus_counts_plot.rds
│   │   ├── CTSS_correlations_matrix.rds
│   │   ├── CTSS_correlations_plot.pdf
│   │   ├── CTSS_correlations_plot.rds
│   │   ├── CTSS_pca_plot.pdf
│   │   ├── CTSS_pca_plot.rds
│   │   ├── dinucleotide_frequencies_plot.pdf
│   │   ├── dinucleotide_frequencies_plot.rds
│   │   ├── enhancer_count_per_sample_plot.pdf
│   │   ├── enhancer_count_per_sample_plot.rds
│   │   ├── enhancer_expression_pca_plot.pdf
│   │   ├── enhancer_expression_pca_plot.rds
│   │   ├── interquartile_width_tagclusters_plot.pdf
│   │   ├── interquartile_width_tagclusters_plot.rds
│   │   ├── norm_CTSS_correlations_matrix.rds
│   │   ├── norm_CTSS_correlations_plot.pdf
│   │   ├── norm_CTSS_correlations_plot.rds
│   │   ├── reverse_cumulative_plot.pdf
│   │   ├── reverse_cumulative_plot.rds
│   │   ├── <sample_name_1>\_tagcluster_dominantTSSlogos_plot.pdf
│   │   ├── <sample_name_1>\_tagcluster_dominantTSSlogos_plot.rds
│   │   ├── <sample_name_2>\_tagcluster_dominantTSSlogos_plot.pdf
│   │   ├── <sample_name_2>\_tagcluster_dominantTSSlogos_plot.rds
│   │   ├── sample_tag_cluster_count.txt
│   │   ├── tag_clusters_counts_plot.pdf
│   │   ├── tag_clusters_counts_plot.rds
│   │   ├── tag_region_annotation_plot.pdf
│   │   └── tag_region_annotation_plot.rds
│   ├── tables
│   │   ├── consensus_cluster_per_sample_ctss.csv
│   │   ├── consensus_clusters_tpm.csv
│   │   └── enhancer_expression_per_sample.tsv
│   ├── tracks
│   │   ├── consensusClusters.bed
│   │   ├── enhancers.bed
│   │   ├── <sample_name_1>\_normalized_minus.bw
│   │   ├── <sample_name_1>\_normalized_plus.bw
│   │   ├── <sample_name_1>\_raw_minus.bw
│   │   ├── <sample_name_1>\_raw_plus.bw
│   │   ├── <sample_name_1>\_tagClusters.bed
│   │   ├── <sample_name_2>\_normalized_minus.bw
│   │   ├── <sample_name_2>\_normalized_plus.bw
│   │   ├── <sample_name_2>\_raw_minus.bw
│   │   ├── <sample_name_2>\_raw_plus.bw
│   │   └── <sample_name_2>\_tagClusters.bed
│   └── versions.yml
├── cat_fastq
│   ├── <sample_name_1>\_1.merged.fastq.gz
│   ├── <sample_name_1>\_2.merged.fastq.gz
│   ├── <sample_name_2>\_1.merged.fastq.gz
│   └── <sample_name_2>\_2.merged.fastq.gz
├── chrom_sizes_and_fai
│   ├── <genome_name>.fa.fai
│   ├── <genome_name>.fa.sizes
│   └── versions.yml
├── cutadapt
│   ├── <sample_name_1>.cutadapt.log
│   ├── <sample_name_1>\_R1_gtrimmed.fastq.gz
│   ├── <sample_name_1>\_R2_gtrimmed.fastq.gz
│   ├── <sample_name_2>.cutadapt.log
│   ├── <sample_name_2>\_R1_gtrimmed.fastq.gz
│   ├── <sample_name_2>\_R2_gtrimmed.fastq.gz
│   └── versions.yml
├── fastqc
│   ├── <sample_name_1>\_1_fastqc.html
│   ├── <sample_name_1>\_1_fastqc.zip
│   ├── <sample_name_1>\_2_fastqc.html
│   ├── <sample_name_1>\_2_fastqc.zip
│   ├── <sample_name_2>\_1_fastqc.html
│   ├── <sample_name_2>\_1_fastqc.zip
│   ├── <sample_name_2>\_2_fastqc.html
│   ├── <sample_name_2>\_2_fastqc.zip
│   └── versions.yml
├── multiqc
│   ├── multiqc_data
│   │   ├── mqc_cutadapt_filtered_reads_plot_1.txt
│   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Counts.txt
│   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Obs_Exp.txt
│   │   ├── mqc_fastqc_adapter_content_plot_1.txt
│   │   ├── mqc_fastqc_overrepresented_sequences_plot_1.txt
│   │   ├── mqc_fastqc_overrepresented_sequences_plot-2_1.txt
│   │   ├── mqc_fastqc_per_base_n_content_plot_1.txt
│   │   ├── mqc_fastqc_per_base_n_content_plot-2_1.txt
│   │   ├── mqc_fastqc_per_base_sequence_quality_plot_1.txt
│   │   ├── mqc_fastqc_per_base_sequence_quality_plot-2_1.txt
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Counts.txt
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Percentages.txt
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Counts.txt
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Percentages.txt
│   │   ├── mqc_fastqc_per_sequence_quality_scores_plot_1.txt
│   │   ├── mqc_fastqc_per_sequence_quality_scores_plot-2_1.txt
│   │   ├── mqc_fastqc_sequence_counts_plot_1.txt
│   │   ├── mqc_fastqc_sequence_counts_plot-2_1.txt
│   │   ├── mqc_fastqc_sequence_duplication_levels_plot_1.txt
│   │   ├── mqc_fastqc_sequence_duplication_levels_plot-2_1.txt
│   │   ├── mqc_fastqc_sequence_length_distribution_plot_1.txt
│   │   ├── mqc_samtools_alignment_plot_1.txt
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Normalised_Counts.txt
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Observed_over_Expected_Counts.txt
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Raw_Counts.txt
│   │   ├── mqc_star_alignment_plot_1.txt
│   │   ├── multiqc_citations.txt
│   │   ├── multiqc_cutadapt.txt
│   │   ├── multiqc_data.json
│   │   ├── multiqc_fastqc_1.txt
│   │   ├── multiqc_fastqc.txt
│   │   ├── multiqc_general_stats.txt
│   │   ├── multiqc.log
│   │   ├── multiqc_samtools_flagstat.txt
│   │   ├── multiqc_samtools_idxstats.txt
│   │   ├── multiqc_samtools_stats.txt
│   │   ├── multiqc_sources.txt
│   │   └── multiqc_star.txt
│   ├── multiqc_plots
│   │   ├── pdf
│   │   │   ├── mqc_cutadapt_filtered_reads_plot_1_pc.pdf
│   │   │   ├── mqc_cutadapt_filtered_reads_plot_1.pdf
│   │   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Counts.pdf
│   │   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Obs_Exp.pdf
│   │   │   ├── mqc_fastqc_adapter_content_plot_1.pdf
│   │   │   ├── mqc_fastqc_overrepresented_sequences_plot_1.pdf
│   │   │   ├── mqc_fastqc_overrepresented_sequences_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_per_base_n_content_plot_1.pdf
│   │   │   ├── mqc_fastqc_per_base_n_content_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_per_base_sequence_quality_plot_1.pdf
│   │   │   ├── mqc_fastqc_per_base_sequence_quality_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Counts.pdf
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Percentages.pdf
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Counts.pdf
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Percentages.pdf
│   │   │   ├── mqc_fastqc_per_sequence_quality_scores_plot_1.pdf
│   │   │   ├── mqc_fastqc_per_sequence_quality_scores_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_sequence_counts_plot_1_pc.pdf
│   │   │   ├── mqc_fastqc_sequence_counts_plot_1.pdf
│   │   │   ├── mqc_fastqc_sequence_counts_plot-2_1_pc.pdf
│   │   │   ├── mqc_fastqc_sequence_counts_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_sequence_duplication_levels_plot_1.pdf
│   │   │   ├── mqc_fastqc_sequence_duplication_levels_plot-2_1.pdf
│   │   │   ├── mqc_fastqc_sequence_length_distribution_plot_1.pdf
│   │   │   ├── mqc_samtools_alignment_plot_1_pc.pdf
│   │   │   ├── mqc_samtools_alignment_plot_1.pdf
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Normalised_Counts.pdf
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Observed_over_Expected_Counts.pdf
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Raw_Counts.pdf
│   │   │   ├── mqc_star_alignment_plot_1_pc.pdf
│   │   │   └── mqc_star_alignment_plot_1.pdf
│   │   ├── png
│   │   │   ├── mqc_cutadapt_filtered_reads_plot_1_pc.png
│   │   │   ├── mqc_cutadapt_filtered_reads_plot_1.png
│   │   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Counts.png
│   │   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Obs_Exp.png
│   │   │   ├── mqc_fastqc_adapter_content_plot_1.png
│   │   │   ├── mqc_fastqc_overrepresented_sequences_plot_1.png
│   │   │   ├── mqc_fastqc_overrepresented_sequences_plot-2_1.png
│   │   │   ├── mqc_fastqc_per_base_n_content_plot_1.png
│   │   │   ├── mqc_fastqc_per_base_n_content_plot-2_1.png
│   │   │   ├── mqc_fastqc_per_base_sequence_quality_plot_1.png
│   │   │   ├── mqc_fastqc_per_base_sequence_quality_plot-2_1.png
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Counts.png
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Percentages.png
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Counts.png
│   │   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Percentages.png
│   │   │   ├── mqc_fastqc_per_sequence_quality_scores_plot_1.png
│   │   │   ├── mqc_fastqc_per_sequence_quality_scores_plot-2_1.png
│   │   │   ├── mqc_fastqc_sequence_counts_plot_1_pc.png
│   │   │   ├── mqc_fastqc_sequence_counts_plot_1.png
│   │   │   ├── mqc_fastqc_sequence_counts_plot-2_1_pc.png
│   │   │   ├── mqc_fastqc_sequence_counts_plot-2_1.png
│   │   │   ├── mqc_fastqc_sequence_duplication_levels_plot_1.png
│   │   │   ├── mqc_fastqc_sequence_duplication_levels_plot-2_1.png
│   │   │   ├── mqc_fastqc_sequence_length_distribution_plot_1.png
│   │   │   ├── mqc_samtools_alignment_plot_1_pc.png
│   │   │   ├── mqc_samtools_alignment_plot_1.png
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Normalised_Counts.png
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Observed_over_Expected_Counts.png
│   │   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Raw_Counts.png
│   │   │   ├── mqc_star_alignment_plot_1_pc.png
│   │   │   └── mqc_star_alignment_plot_1.png
│   │   └── svg
│   │   ├── mqc_cutadapt_filtered_reads_plot_1_pc.svg
│   │   ├── mqc_cutadapt_filtered_reads_plot_1.svg
│   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Counts.svg
│   │   ├── mqc_cutadapt_trimmed_sequences_plot_3_Obs_Exp.svg
│   │   ├── mqc_fastqc_adapter_content_plot_1.svg
│   │   ├── mqc_fastqc_overrepresented_sequences_plot_1.svg
│   │   ├── mqc_fastqc_overrepresented_sequences_plot-2_1.svg
│   │   ├── mqc_fastqc_per_base_n_content_plot_1.svg
│   │   ├── mqc_fastqc_per_base_n_content_plot-2_1.svg
│   │   ├── mqc_fastqc_per_base_sequence_quality_plot_1.svg
│   │   ├── mqc_fastqc_per_base_sequence_quality_plot-2_1.svg
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Counts.svg
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot-2_Percentages.svg
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Counts.svg
│   │   ├── mqc_fastqc_per_sequence_gc_content_plot_Percentages.svg
│   │   ├── mqc_fastqc_per_sequence_quality_scores_plot_1.svg
│   │   ├── mqc_fastqc_per_sequence_quality_scores_plot-2_1.svg
│   │   ├── mqc_fastqc_sequence_counts_plot_1_pc.svg
│   │   ├── mqc_fastqc_sequence_counts_plot_1.svg
│   │   ├── mqc_fastqc_sequence_counts_plot-2_1_pc.svg
│   │   ├── mqc_fastqc_sequence_counts_plot-2_1.svg
│   │   ├── mqc_fastqc_sequence_duplication_levels_plot_1.svg
│   │   ├── mqc_fastqc_sequence_duplication_levels_plot-2_1.svg
│   │   ├── mqc_fastqc_sequence_length_distribution_plot_1.svg
│   │   ├── mqc_samtools_alignment_plot_1_pc.svg
│   │   ├── mqc_samtools_alignment_plot_1.svg
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Normalised_Counts.svg
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Observed_over_Expected_Counts.svg
│   │   ├── mqc_samtools-idxstats-mapped-reads-plot_Raw_Counts.svg
│   │   ├── mqc_star_alignment_plot_1_pc.svg
│   │   └── mqc_star_alignment_plot_1.svg
│   └── multiqc_report.html
├── pipeline_info
│   ├── execution_report_2025-06-20_09-00-09.html
│   ├── execution_timeline_2025-06-20_09-00-09.html
│   ├── execution_trace_2025-06-20_09-00-09.txt
│   ├── pipeline_dag_2025-06-20_09-00-09.html
│   └── software_versions.yml
├── samtools_flagstat
│   ├── <sample_name_1>\_sorted.bam.flagstat
│   ├── <sample_name_2>\_sorted.bam.flagstat
│   └── versions.yml
├── samtools_idxstats
│   ├── <sample_name_1>\_sorted.bam.idxstats
│   ├── <sample_name_2>\_sorted.bam.idxstats
│   └── versions.yml
├── samtools_index
│   ├── <sample_name_1>\_sorted.bam.bai
│   ├── <sample_name_2>\_sorted.bam.bai
│   └── versions.yml
├── samtools_sort
│   ├── <sample_name_1>\_sorted.bam
│   ├── <sample_name_2>\_sorted.bam
│   └── versions.yml
├── samtools_stats
│   ├── <sample_name_1>.stats
│   └── versions.yml
├── star_align
│   ├── <sample_name_1>.Aligned.sortedByCoord.out.bam
│   ├── <sample_name_1>.Log.final.out
│   ├── <sample_name_1>.Log.out
│   ├── <sample_name_1>.Log.progress.out
│   ├── <sample_name_1>.Signal.UniqueMultiple.str1.out.wig
│   ├── <sample_name_1>.Signal.UniqueMultiple.str2.out.wig
│   ├── <sample_name_1>.Signal.Unique.str1.out.wig
│   ├── <sample_name_1>.Signal.Unique.str2.out.wig
│   ├── <sample_name_1>.SJ.out.tab
│   ├── <sample_name_2>.Aligned.sortedByCoord.out.bam
│   ├── <sample_name_2>.Log.final.out
│   ├── <sample_name_2>.Log.out
│   ├── <sample_name_2>.Log.progress.out
│   ├── <sample_name_2>.Signal.UniqueMultiple.str1.out.wig
│   ├── <sample_name_2>.Signal.UniqueMultiple.str2.out.wig
│   ├── <sample_name_2>.Signal.Unique.str1.out.wig
│   ├── <sample_name_2>.Signal.Unique.str2.out.wig
│   ├── <sample_name_2>.SJ.out.tab
│   └── versions.yml
├── star_genomegenerate
│   ├── star
│   │   ├── chrLength.txt
│   │   ├── chrNameLength.txt
│   │   ├── chrName.txt
│   │   ├── chrStart.txt
│   │   ├── exonGeTrInfo.tab
│   │   ├── exonInfo.tab
│   │   ├── geneInfo.tab
│   │   ├── Genome
│   │   ├── genomeParameters.txt
│   │   ├── Log.out
│   │   ├── SA
│   │   ├── SAindex
│   │   ├── sjdbInfo.txt
│   │   ├── sjdbList.fromGTF.out.tab
│   │   ├── sjdbList.out.tab
│   │   └── transcriptInfo.tab
│   └── versions.yml
├── trimgalore
│   ├── <sample_name_1>\_1.fastq.gz_trimming_report.txt
│   ├── <sample_name_1>\_1_val_1_fastqc.html
│   ├── <sample_name_1>\_1_val_1_fastqc.zip
│   ├── <sample_name_1>\_1_val_1.fq.gz
│   ├── <sample_name_1>\_2.fastq.gz_trimming_report.txt
│   ├── <sample_name_1>\_2_val_2_fastqc.html
│   ├── <sample_name_1>\_2_val_2_fastqc.zip
│   ├── <sample_name_1>\_2_val_2.fq.gz
│   ├── <sample_name_2>\_1.fastq.gz_trimming_report.txt
│   ├── <sample_name_2>\_1_val_1_fastqc.html
│   ├── <sample_name_2>\_1_val_1_fastqc.zip
│   ├── <sample_name_2>\_1_val_1.fq.gz
│   ├── <sample_name_2>\_2.fastq.gz_trimming_report.txt
│   ├── <sample_name_2>\_2_val_2_fastqc.html
│   ├── <sample_name_2>\_2_val_2_fastqc.zip
│   ├── <sample_name_2>\_2_val_2.fq.gz
│   └── versions.yml
└── txdb
    ├── annotation_from_gtf.sqlite
    └── versions.yml

Outputs from mapping

cat_fastq folder with the input fastq files, merged by sample in case they were separated into different lanes. fastqc folder with the results of the intitial quality check (before trimming or filtering). Currently it is not included in the MultiQC report. cutadapt folder with the output from trimming the 5’ G. trimgalore folder with the output of TrimGalore! including adapter trimming and FastQC report (this one is included in the MultiQC report). star_genomegenerate folder with the outpue of the STAR genomegenerate mode which creates the genome indeces. chrom_sizes_and_fai folder with the genome index and chromosome sizes. star_align folder with the output of STAR aligner: bam files, wig files of uniquely mapped and multi-mapped (the unique_only parameter defines whether the uniqely mapped wigs or the multi-mapped wigs are used downstream), tab file, and logs. bigwig folder with the mapped reads in bigwig format. samtools_sort folder with the sorted bam files. samtools_index folder with the indexed bam files. samtools_stats folder with the outputs from the stat command of samtools run after mapping. samtools_flagstat folder with the outputs from the flagstat command of samtools run after mapping. samtools_idxstats folder with the outputs from the idxstat command of samtools run after mapping. multiqc folder with the data and plots, and the report of the mapping summary. pipeline_info folder storing software versions and logs.

MultiQC

Output files

multiqc/
- multiqc_report.html: a standalone HTML file that can be viewed in your web browser.
- multiqc_data/: directory containing parsed statistics from the different tools used in the pipeline.
- multiqc_plots/: directory containing static images from the report in various formats.

MultiQC is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.

Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see http://multiqc.info.

Outputs from CAGEr and CAGEfightR

txdb folder with the sqlite file of the TxDb file generated from the user provided gtf file. cager folder with the cager_report.html file including the QC plots, with the respective user-provided parameters and descriptions. If the final set of called enhancers is empty, the corresponding plots shown in the report are replaced with placeholders saying “No enhancers found”. The folder also includes multiple subfolders as listed below with the intermediate files, tables, tracks, and plots in pdf format.

cager/intermediate_cagerobj folder stores 5 different RDS files.
- initial_cagexp.rds stores the data right after reading in of the mapped bigwig/bam files
- annotated_cagexp.rds stores the data after it has been annotated.
- normalized_clustered_cagexp.rds stores the data after it has been normalized, tag clusters, and consensus clusters called.
- supported_enhancers.rds is the intermediate output of the CAGEfightR enhancer calling script. This inlcudes all enhancers that are called with support from the user defined number of samples.
- nonTSS_enhancers.rds is the final output of the enhancer calling script. It is different from the supported_enhancers.rds as the nonTSS_enhancers.rds lists the enhancers that are not overlapping any of the consensus clusters identified by CAGEr.
cager/plots folder stores the different plots and RDS files for the report. It also includes the TSS logos saved in the <sample_name>_tagcluster_dominantTSSlogos_plot.pdf file. Note: when reading in plots from RDS it is a good idea to import magrittr first, otherwise the plot content text is written out instead of the actual plot.
cager/tables folder stores 3 csv files.
- consensus_clusters_tpm.csv file stores the dataframe which is directly exported from CAGEr consensus clusters matching the scores provided in consensusClustersTpm(ce). Rows are the consensus cluster regions and columns are the samples.
- consensus_cluster_per_sample_ctss.csv files stores a dataframe that has the same structure as consensus_clusters_tpm.csv but instead of the scores defined by the overlapping TagCluster scores, consensus_cluster_per_sample_ctss.csv includes the scores caclulated by including all CTSS scores overlapping the consensus clusters. As tag clusters has already been filtered by a tpm threshold, the CTSS scores is higher or equal to the tag cluster scores. This is the preferred output for downstream analysis.
- enhancer_expression_per_sample.tsv file stores a dataframe with the enhancer regions as rows and samples as columns. The values are tpm normalized CTSS scores.
cager/tracks folder stores bed and bigwig files exported after identifying CTSS (raw strand specific bigwig), normalizing CTSS (normalized strand specific bigwig), tag clusters (bed), consensus clusters (bed), and enhancers (bed).

Pipeline information

Output files

pipeline_info/
- Reports generated by Nextflow: execution_report.html, execution_timeline.html, execution_trace.txt and pipeline_dag.dot/pipeline_dag.svg.
- Reports generated by the pipeline: pipeline_report.html, pipeline_report.txt and software_versions.yml. The pipeline_report* files will only be present if the --email / --email_on_fail parameter’s are used when running the pipeline.
- Parameters used by the pipeline run: params.json.

Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.

Details about Nextflow

The pipeline will produce a directory with results (by default, called results) and a directory for intermediate files (by default, called work) in the directory where it is launched. If running the pipeline sequentially on different raw datasets (for example, on data from different species), make sure to launch each run from a different directory, so that the next run does not overwrite the results of the previous run. However, if you plan to run two or more instances of the pipeline in parallel, using the same storage, then, apart from running them from different directories, you also must provide a different name for each work directory using the -w option.

Since Nextflow work directories can quickly become very large and do not need to be backed-up (but removed after a successful run, instead!), a good practice is to create work directories in a dedicated storage space that gets cleaned once in a while and is usually called a “scratch” space. Make sure to check the documentation of your cluster/server or to ask your system administrator on where you should create Nextflow work directories.

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