- PAMLINC is a workflow for processing raw RNA-Seq Illumina data for rapid quantification of transcript abundance, annotation of RNA modifications, and Long non-coding Intergenic ribonucleotides (lincRNA).
- PAMLINC can process raw FASTQ files containing either paired-end or single-end reads. It can also process sequence read archive (SRA) from NCBI using a SRA ID. PAMLINC supports two reads trimming options: trimmomatic and fastp. PAMLINC also supports two reads aligner options: TopHat2 and STAR, but users who are interested in using PAMLINC to annotate RNA modification must select TopHat2 as the aligner of choice. This is due to alignment algorithms compatibility.
- PAMLINC minimally requires the following input data:
- Reference genome (FASTA)
- Reference annotation (GTF/GFF3)
- RNA-Seq reads (FASTQ) - Paired-end or Single end or NCBI SRA ID.
- Optional files: The -i flag allows users to provide a reference genome index folder containing the genome index files for either bowtie2, STAR, or both, depending on the user's aligner of choice. The STAR index folder should be named 'star_index' and it should be a subdirectory of the reference genome index folder provided. PAMLINC automatically generates the reference genome index files for both bowtie2 and STAR when the user does not provide it, but this increases the run time of PAMLINC.
- Output: When run with all three flags (-m, -e, -q), PAMLINC generates four folders in the output directory. The folders are <sample_name>_HAMR, <sample_name>_lincRNA, intermediate_files, and transcript_abund_quant
| Argument | Description |
|---|---|
| -g | reference genome fasta file |
| -a | reference genome annotation file |
| -i | reference genome index folder |
| -l | library type (fr-unstranded, fr-firststrand, or fr-secondstrand). If you are unsure of the library type of your reads, you can infer it using salmon. |
| -1 | read_1 |
| -2 | read_2 |
| -u | single_read |
| -o | output directory |
| -S | NCBI SRA-ID #upper case S |
| -p | number of threads, default=4 |
| -q | activate transcript abundance quantification option |
| -M | select aligner of choice ("tophat2" or "star"), include double quotation on the command line. Must select tophat2 if you want to run HAMR |
| -t | select adapter trimmer of choice ("trimmomatic" or "fastp"), include double quotation on the command line. |
| -c | sjdbOverhang #Required for STAR aligner. Value is dependent on the read length of your fastq files (read length minus 1) |
| -f | genomeSAindexNbases #Required for STAR aligner, default=14 but it should be scaled down for small genomes, with a typical value of min(14, log2(GenomeLength)/2 - 1) |
| -y | type of read (single end or paired-end) #Denoted as "SE" or "PE", include double quotation on command line |
| -d | reads_mismatches (% reads mismatches to allow) #Required for TopHat2 aligner |
| -m | activates HAMR for RNA modification annotation |
| -A | minimum base calling quality score. All low-quality bases will be removed from HAMR analysis, default=30 |
| -B | minimum read coverage of a genomic position for it to be analyzed in HAMR, default=10 |
| -F | expected percentage of mismatches based solely on sequencing error, default=0.01 |
| -G | maximum p-value cutoff. All sites with a P-value greater than this value will be filtered out during HAMR analysis, default=1 |
| -H | maximum FDR cutoff, default=0.05 |
| -I | minimum % of reads that must match the reference nucleotide. All sites with reference read nucleotide proportion less than this value will be filtered out during HAMR analysis, default=0.05 |
| -e | activates evolinc_i for lincRNA identification |
| -E | run evolinc_i with mandatory files or both mandatory and optional files. Denoted as "M" or "MO", include double quotation on the command line, default="M" |
| -T | </path/to/transposable Elements file> (optional file for evolinc_i) |
| -C | </path/to/CAGE RNA file> (optional file for evolinc_i) |
| -D | </path/to/known lincRNA file> (optional file for evolinc_i) |
| -k | feature_type #Feature type (Default is exon) #Required for featureCount |
| -r | gene attribute (default=gene_id) #Required for featureCount |
| -n | strandedness (default=0 (unstranded), 1 (stranded), 2 (reversely stranded) #Required for featureCount |
| -h | help message |
- Linux-based computer, server, or cluster.
- Docker
#pull docker image for PAMLINC:
docker pull chosenobih/pamlinc:v0.4
#download genome file for sorghum bicolor from CyVerse data store
wget https://data.cyverse.org/dav-anon/iplant/home/chosen/pamlinc_files/sbicolor.fa
#download genome annotation file for sorghum bicolor from CyVerse data store
wget https://data.cyverse.org/dav-anon/iplant/home/chosen/pamlinc_files/sbicolor.gff3
#download sbicolor genome index files for bowtie-2 from google drive. Copy the link and paste it into your browser.
https://drive.google.com/drive/folders/1EazCZ1__K7DCKbOOYoQ8jeqj3Tpb9KrR?usp=sharing
Running pamlinc in paired-end mode with a fastq file
#download sample data from CyVerse data store:
#R1
wget https://data.cyverse.org/dav-anon/iplant/home/chosen/pamlinc_files/sample_1_R1.fastq.gz
#download sample data from CyVerse data store:
#R2
wget https://data.cyverse.org/dav-anon/iplant/home/chosen/pamlinc_files/sample_1_R2.fastq.gz
#run pamlinc to annotate RNA modification, identify lincRNA and quantify transcript abundance with paired fastq.gz files. These options can be turned on or off using different flags.
docker run --rm -v $(pwd):/working-dir -w /working-dir chosenobih/pamlinc:v0.4 -a sbicolor.gff3 -g sbicolor.fa -o pamlinc_result_PE -y "PE" -p 6 -t "trimmomatic" -M "tophat2" -l fr-secondstrand -q -e -E "M" -m -k exon -r gene_id -n 0 -d 12 -1 sample_1_R1.fastq.gz -2 sample_1_R2.fastq.gz -i index_folder
#download paired-end sample run output from google drive. Copy the link and paste it into your browser.
https://drive.google.com/drive/folders/1A4CuPfrvX0oBw2cmqn8wOBI9_rMWdds0?usp=sharing
Running pamlinc in single-end mode with a fastq file
#download sample data from CyVerse data store:
wget https://data.cyverse.org/dav-anon/iplant/home/chosen/pamlinc_files/sample_1_SE.fastq.gz
#run pamlinc to annotate RNA modification, identify lincRNA and quantify transcript abundance with paired fastq.gz files. These options can be turned on or off using different flags.
docker run --rm -v $(pwd):/working-dir -w /working-dir chosenobih/pamlinc:v0.4 -a sbicolor.gff3 -g sbicolor.fa -o pamlinc_result_SE -y "SE" -p 6 -t "trimmomatic" -M "tophat2" -l fr-secondstrand -q -e -E "M" -m -k exon -r gene_id -n 0 -d 12 -u sample_1_SE.fastq.gz -i index_folder
#download single-end sample run output from google drive. Copy the link and paste it into your browser.
https://drive.google.com/drive/folders/1iLB7Gec9qB6Sv2TyFlHM_GG3HQ7wPWa9?usp=sharing
Running pamlinc in paired-end mode with an SRA-ID
#run pamlinc to annotate RNA modification, identify lincRNA and quantify transcript abundance with paired fastq.gz files. These options can be turned on or off using different flags.
docker run --rm -v $(pwd):/working-dir -w /working-dir chosenobih/pamlinc:v0.4 -a sbicolor.gff3 -g sbicolor.fa -o pamlinc_result_SRA-ID_PE -y "PE" -p 6 -t "trimmomatic" -M "tophat2" -S SRR18095197 -l fr-secondstrand -q -e -E "M" -m -k exon -r gene_id -n 0 -d 12 -i index_folder
Running pamlinc in single-end mode with an SRA-ID
#run pamlinc to annotate RNA modification, identify lincRNA and quantify transcript abundance with paired fastq.gz files. These options can be turned on or off using different flags.
docker run --rm -v $(pwd):/working-dir -w /working-dir chosenobih/pamlinc:v0.4 -a sbicolor.gff3 -g sbicolor.fa -o pamlinc_result_SRA-ID_SE -y "SE" -p 6 -t "trimmomatic" -M "tophat2" -S SRR10376271 -l fr-secondstrand -q -e -E "M" -m -k exon -r gene_id -n 0 -d 12 -i index_folder