In this repository, you will find all the code to reproduce my analysis based on the reads from Singhania et al. (2019) (only lung and blood tissues from wildtype and toxoplasma).
First use fastQC to assess the quality of the reads for the lung and the blood: 01_protocole_Lung and 02_protocole_Bloodto create the fastqc reports, and then use MultiQC to have all your fastqc in one report with command Multiqc . , done in 03_download_gen_specie_+_multiqc.
You will need to download the reference genome from ensembl 03_download_gen_specie_+_multiqc. Then run 04_hist2_index, to avoid download many time, I take it in lland directory.
To do that, run 05_hist2_mapping, 06_sam_to_bam, 07_bam_sort and 08_bam_index Then you will have a .bam and a .bam.bai file for each of your reads.
You will need to download the annotation corresponding to the reference genome you download before. Then run 09_feature_count and 10_Seq2 to get the count table that you will use for the next step. Download it locally.
Then you can run the R script 11_DESeq2_R.
You have the combineHisat2Map to see alignment result.