LOY (Loss of Y Chromosome) Mapping Pipeline

This repository contains scripts and tools to quantify and analyze Loss of Y (LOY) in genomic datasets, primarily from WGS, WES, and RNA-seq data. It is designed for CCLE datasets and other human genomic data sources.

---

Table of Contents

• Overview
• Scripts
• Usage
• Data
• Contributing
• License

---

Overview

Loss of Y (LOY) is a common somatic chromosomal aberration with implications in aging and cancer. This pipeline provides tools to:

• Extract reads mapped to chromosome Y.
• Quantify LOY across samples and tissues.
• Integrate LOY with RNA-seq for differential expression analysis.
• Generate visualizations for LOY patterns.

---

Scripts

ExtractYpositions.sh

Extracts all reads mapped to chromosome Y from a directory of BAM files and records their positions.

Usage:

bash ExtractYpositions.sh /path/to/bam/directory /path/to/output/file.txt

AnalyzeYPositions.R

Analyzes chromosome Y read positions to identify sparse regions and low-density genes.
Generates histograms, cumulative distributions, and visualizations of read density.

Dependencies:

• R packages: dplyr, tidyr, ggplot2

Key outputs:

• ChromosomeDensityHist.png – Histogram of read density across chromosome Y
• low_density_2000genes.txt – Genes overlapping low-density regions (below threshold)
• ChromosomeCDF.png – Cumulative distribution function of read densities
• orderedSamples.txt – Sample IDs ordered by number of sparse regions
• ChromosomePosition.png – Scatter plot of reads per sample, ordered by sparsity
• ChromosomeBinSummary.png – Distribution of reads across chromosome Y bins

Usage:

Rscript AnalyzeYPositions.R

CompareDNAtoRNA.R

Compares DNA sequencing read positions on chromosome Y with RNA-seq expression data for Y-linked genes.
Generates a visualization of expressed Y-linked genes across samples ordered by DNA sparsity.

Dependencies:

• R packages: dplyr, tidyr, ggplot2
• Input files:
  • RNAseqdataClean.txt – Processed RNA-seq expression matrix (GCT-like format)
  • genes_chrY_positions.txt – Start and end positions of Y-linked genes
  • orderedSamples.txt – Sample order generated by AnalyzeYPositions.R
  • Num_mapped_reads.csv – Mapping between Run IDs and cell line names

Key output:

• Gene_vs_Sample_BarsV2.png – Bar plot showing expression presence of Y-linked genes across samples

Usage:

Rscript CompareDNAtoRNA.R

CallVariants.sh

Performs variant calling on BAM files using bcftools and outputs compressed, indexed VCF files.

Dependencies:

• Tools: bcftools (with mpileup, call, and index subcommands)
• Input files:
  • *.bam – BAM files to be processed
  • Homo_sapiens_assembly19.fixed.fasta – Reference genome (update path as needed)

Outputs:

• VCF_Files/ – Directory containing compressed and indexed VCFs (.vcf.gz and .csi)

Usage:

bash CallVariants.sh

makeMatrixEQTL.R

Runs eQTL analysis by integrating SNP genotypes from VCF files with RNA-seq expression data using the MatrixEQTL R package.

Dependencies:

• R packages: VariantAnnotation, dplyr, MatrixEQTL, data.table, Matrix, biomaRt
• Input files:
  • *.vcf.gz – Variant call files (compressed and indexed with bcftools)
  • Num_mapped_reads.csv – Maps sample IDs (Run) to cell lines
  • CCLE_RNAseq_genes_rpkm_20180929.gct – Gene expression data (RNA-seq, RPKM values)
  • snps_positions.txt – SNP positions (generated during runtime)
  • gene_positions.txt – Gene positions (fetched via biomaRt)

Outputs:

• snps_positions.txt – SNP positions extracted from VCFs
• gene_positions.txt – Gene coordinates for tested genes
• output_matrixeqtl_results.txt – eQTL associations (with p-values and FDR correction)

Usage:

Rscript makeMatrixEQTL.R

Data

This repository contains data files required for the LOY mapping pipeline.

Required files

• gene_chrY_positions.txt – Contains the start and end positions of genes on chromosome Y.
• Num_mapped_reads.csv – Maps sequencing run IDs (Run) to their corresponding CCLE cell lines (cell_line).
  • Example format:

    Run,cell_line,num_mapped_reads
    SRR8639150,EBC1_LUNG,379420
    SRR8639204,CAKI1_KIDNEY,541050
    SRR8639219,DMS53_LUNG,514931
    

  • Only the Run and cell_line columns are required for analyses.
• BAM files – High-coverage WGS/WES BAM files.
• RNA-seq counts – Processed RNA-seq count files for integration with LOY analyses.

Full CCLE or other controlled-access datasets are not included due to data usage restrictions.