CTLife / xQTLs

Scripts for various molecular quantitative trait locus (xQTL) analysis.

xQTLs

Scripts for various molecular quantitative trait locus (xQTL) analysis.

All Perl, Python, R, and Bash Shell scripts were used to eQTLs and RNA-m6A QTLs analysis by integrating QTLtools and MASH.

Steps:

1. Quantify reads density from ChIP-seq or MeRIP-seq data by 1a_QTLtools_quan.peaks.pl, or quantify gene expression level from RNA-seq data by 1b_QTLtools_quan.gene.pl. QTLtools quan is invoked in line 125, GTF file may need to be changed based on your file name. More details please see perl 1a_QTLtools_quan.peaks.pl -help or perl 1b_QTLtools_quan.gene.pl -help.

2. Get value log2((FPKM_IP+1)/(FPKM_INPUT+1)) of each peak for each MeRIP-seq sample by 2a_log2ratio.peaks.pl. And get value log2(TPM_INPUT+1) of each gene for each RNA-seq sample (Input of MeRIP-seq) by 2b_log2TPM.gene.pl. More details please see perl xxx.pl -help.

3. Merge all files from each sample into one file to satisfy the input format of QTLtools cis and QTLtools trans by 3a_merge.peaks.pl or 3b_merge.gene.pl. Please ensure that the colomn orders of the GFT file and the merged file are the same. More details please see perl xxx.pl -help.

4. Further filter m6A-epaks or genes by 4a_keptRegions.peaks.R or 4b_keptRegions.gene.R. We can remove peaks or genes with low reads desnity or low variance. More details please see code of 4a_keptRegions.peaks.R or 4b_keptRegions.gene.R

5. PCA for genotype by 5_QTLtools_pca.SNP.sh. PCA and PEER factor analysis for phenotype please see the codes under folder covariates.

6-8. Identify cis- or trans-QTLs by invoking QTLtools cis or QTLtools trans.