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ALIGNEMENT.md

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Quick overview

Here we describe the alignment part of the workflow.

Set up Tools

First you need to check that the following tools are installed on server/computer.

Scripts available here are in Python3.
It's not required but advised to install Conda if python3 is not set up on your computer.
It will make things easier then for installing tools or switching to older python version if needed.

Conda : here

ALIGNMENT :

STAR : Aligner here

Salmon : Compute TPM values from fastq here

Samtools : Bam handler here

wigToBigWig : Include in KentTools suite here

Set up Files

Download fasta sequence of the genome of interest. (Here we use PRIM_ASSEMBLY from GENCODE R25 based on ENSEMBL 85 for Human and GENCODE M15 based on ENSEMBL 90 for Mouse.
Create this file with chromosome files.

conda install pyfaidx
faidx yourgenome.fasta -i chromsizes > yourgenome.genome.sizes

Also you need to create index for STAR :

STAR --runMode genomeGenerate --genomeDir /home/jean-philippe.villemin/mount_archive2/commun.luco/ref/indexes/GRCm38_PRIM_GENCODE_M15/ --genomeFastaFiles /home/jean-philippe.villemin/mount_archive2/commun.luco/ref/genome/GRCm38_PRIM_GENCODE_M15/GRCm38.primary_assembly.genome.fa --runThreadN 30 --sjdbGTFfile /home/jean-philippe.villemin/mount_archive2/commun.luco/ref/genes/GRCm38_PRIM_GENCODE_M15/gencode.vM15.primary_assembly.annotation.gtf

Generate the fasta file index :

samtools faidx reference.fa

This creates a file called reference.fa.fai

Generate the sequence genome.2bit :

faToTwoBit genome.fa genome.2bit

Last step :

Download the transcripts from gencode for your genome version and then inside a dir called transcriptome for instance, you will create indexes for Salmon as follows :

salmon index -t gencode.vM15.transcripts.fa.gz -i gencode.m15.transcripts.index --type quasi -k 31

Set up ConfigFile.json

We use a json file to create a configuration file before doing your alignment.

The json file is a key:value listing which defines all parameters for the pipeline.

  • number of cores used
  • path to output/input directory
  • name of analyse
  • ...

See config directory. You will find an example called paired.set1_align.json for a test dataset.

Launch Alignment

	python3 pathTo/alignment.py -c pathToConfigFile/condition.json

You can test the pipeline on a short dataset provided in test directory.

It will launch an alignment with STAR. It will creates a directory (path defined in your configuration file) with inside :

  1. Bam file.
  2. Bigwig files per strand normalized by CPM (count per millions) for visualization purpose in UCSC.
  3. Reads count per gene - Sample_ReadsPerGene.tab (used for the gene expression step).
  4. Intermediate files used in the following steps of the pipeline.

You need to use this on each sample/replicate.

Finally you get the following directories as output :

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