RNA-Seq analysis on sapelo2 at UGA

Tsai lab RNA-Seq script

Description

RNA-Seq runs transcriptomic analysis. The input of this pipeline is a csv file. So to begin, prepare a table with the schema like sample_table.csv. This script will then run the RNA-Seq pipeline on the samples from different species in the table.

Here's how the pipeline flows:

It will create folder structure like:

RNA-Seq/data
|
 ----- {species_id}
        |
         ----- fastq (raw fastq files)
         ----- reference (genome reference from Phytozome or other sources)
               |
                ----- species_genome.fasta -> genome.fa
                ----- species_annotation.gff3 -> gene.gtf
        ----- clean (filtered reads)
        ----- map (alignment maps)
        ----- count (quantification results for further analysis)
        ----- miscelaneous
              |
               ----- *.txt
               ----- log....
        ----- file.list
        ----- start.sh
        ----- map.sh
        ----- get_trim_sum.py

Instructions to Run

1. clone this repo

git clone https://github.com/TsailabBioinformatics/RNA-Seq.git;cp RNA-Seq/* .

• if cloning returned fatal: Authentication failed, then try again using a github personal access token. instructions to do so can be found here: https://docs.github.com/en/enterprise-server@3.1/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token

2. create an input csv file (like sample_table.csv), name it input.csv, and add it to RNA-Seq/input/

• check to make sure input.csv exists within the folder RNA-Seq/input

4. change directories into RNA-Seq
5. load modules python-utils and pandas with commands:

ml python-utils

ml pandas

7. run the pipeline

python3 pipeline.py

8. browse specific species' data by changing directories into a species folder:

cd data/{species_id}

TODO - implement visualization --> add instructions to run visualization