EV-RNA-Profiler Manual

This pipeline ": run_SMARTer_pipe_EV_RNA_seq_v3.sh" processes SMARTer Stranded EV RNA-seq data from raw FASTQ files through multiple steps, including quality control, UMI extraction, adapter/quality trimming, rRNA detection, alignment, deduplication, and final feature counting. It also provides a 14-bp motif analysis of Read2, as well as optional bigWig coverage tracks and circular RNA detection (CIRCexplorer2).

1. Usage:

bash run_SMARTer_pipe_EV_RNA_seq_v3_ZYY.sh <R1.fastq.gz> <R2.fastq.gz>

• SampleName: A short identifier for your sample, e.g. B4_TDP43_KD_caRNA_rep3.
• R1.fastq.gz: Path to Read1 FASTQ file (possibly gzipped).
• R2.fastq.gz: Path to Read2 FASTQ file (possibly gzipped). The script creates _processed/ with all outputs.

2. Requirements:

• Linux environment
• Tools: fastqc, multiqc, umi_tools, cutadapt, trim_galore, ribodetector_cpu, seqtk, kraken2, KronaTools, kreport2krona.py, STAR, samtools, bamCoverage, computeMatrix, plotProfile, featureCounts, CIRCexplorer2, python scripts.

3. Description of Steps:

• Step 1: QC + 14-bp R2 motif with get_SMARTer_Read2_14BP_motif.py
• Step 2: UMI extraction + adapter trimming
• Step 3: rRNA detection (ribodetector_cpu)
• Step 4: Kraken classification
• Step 5: STAR alignment
• Step 6: UMI dedup
• Step 7: bigWig coverage and DeepTools
• Step 8: featureCounts
• Step 9: CIRCexplorer2

4. Example Command:

bash run_SMARTer_pipe_EV_RNA_seq_v3_ZYY.sh B4_TDP43_KD_caRNA_rep3 R1.fq.gz R2.fq.gz

5. Output Structure:

• 1_raw_QC_and_motif/: QC reports + motif results
• 2_UMI_trim/: trimmed data + logs
• 3_ribodetector/: rRNA reads
• 4_kraken/: downsampled fastqs + classification
• 5_STAR/: Aligned.sortedByCoord.out.bam etc.
• 6_umi_dedup_bam/: final deduplicated BAM
• 7_bw_density/: bigWig coverage + matrix + profile
• 8_featurecounts/: featureCounts
• 9_CIRCexplorer2/: back-spliced junction + annotated circular RNAs

Enjoy your EV RNA-seq pipeline!