matRseq

mature tRNA sequencing

Setting up the environment

Use the following command to create a conda environment with the essential packages used by matRseq.

conda env create --file=matRseq.yaml
conda activate matRseq

Run matRseq.

Create the metadata file

The metadata file resides in the working directory and lists the required information for each sample. For example:

Sample.name	Sample.prefix	R1	R2	sample.type	cell.line	sample.rep
SW480_LVM2_ribo_r1	SW480_LVM2_ribo_6_S15	SW480_LVM2_ribo_6_S15_R1_001.fastq.gz	SW480_LVM2_ribo_6_S15_R2_001.fastq.gz	ribo	SW480-Par	1
SW480_LVM2_ribo_r2	SW480_LVM2_ribo_7_S16	SW480_LVM2_ribo_7_S16_R1_001.fastq.gz	SW480_LVM2_ribo_7_S16_R2_001.fastq.gz	ribo	SW480-Par	2
SW480_P_total_r1	SW480_P_total_6_S9	SW480_P_total_6_S9_R1_001.fastq.gz	SW480_P_total_6_S9_R2_001.fastq.gz total	SW480-LvM2	1
SW480_P_total_r2	SW480_P_total_7_S10	SW480_P_total_7_S10_R1_001.fastq.gz	SW480_P_total_7_S10_R2_001.fastq.gz	total	SW480-LvM2	2

human mature tRNA reference included in the package

Run the analysis

For bi-variate analysis the following command will run the analysis:

python matRseq.py --runMode metadata.txt 'sample.type~cell.line'  output.txt

and for uni-variate analysis the following command will run the analysis(reference must be specified):

python matRseq.py --runMode --ref=SW480Par metadata_univariate.txt '~cell.line'  output.txt

Options

Run python matRseq.py for usage. The following are the options:

1. --runMode or -r vs --printMode or -p : --printMode prints all the commands that are run
2. -a or --aligner: Choose aligner package (default is BWA)
3. -l or --read : R1, R2, both; Use both R1 and R2 (miSeq) as opposed to R2 (10X). Default is R2
4. --hasUMI vs --noUMI: Whether reads contain UMI or not (Default is hasUMI)
5. --paired vs --single : if the reads are paired end. (Default is paired)
6. --ref: The sample that is the reference in univariate analysis.