# Beyond blacklists: a critical assessment of exclusion set generation strategies and alternative approaches

## TL;DR

This paper evaluates methods to reduce alignment artifacts in genomic data, comparing blacklist strategies with sponge sequences and improved genome assemblies.

## Contribution

The study introduces sponge sequences and the T2T-CHM13 assembly as effective alternatives to traditional blacklists for reducing alignment artifacts.

## Key findings

- Pre-generated exclusion sets are hard to reproduce due to sensitivity to input data and aligner choice.
- Using sponge sequences in alignment reduced ChIP-seq signal correlation as effectively as blacklists while preserving biological signal.
- Sponge-based alignment had minimal impact on RNA-seq gene counts, showing broader utility.

## Abstract

Short-read sequencing data can be affected by alignment artifacts in certain genomic regions. Removing reads overlapping these exclusion regions, previously known as Blacklists, help to potentially improve biological signal. Alternatively, “sponge” or decoy sequences have been proposed to reduce alignment artifacts.

We examined the widely used Blacklist software and found that pre-generated exclusion sets were difficult to reproduce due to sensitivity to input data, aligner choice, and read length. We further explored the use of “sponge” sequences—unassembled genomic regions such as satellite DNA, ribosomal DNA, and mitochondrial DNA—as an alternative approach. We additionally investigated the effect of the T2T-CHM13 genome assembly on improving biological signals. Aligning reads to a genome that includes sponge sequences reduced signal correlation in ChIP-seq data comparably to Blacklist-derived exclusion sets while preserving biological signal. Sponge-based alignment also had minimal impact on RNA-seq gene counts, suggesting broader applicability beyond chromatin profiling. These results highlight the limitations of fixed exclusion sets, and recommend the use of the T2T-CHM13 assembly or, for the hg38 genome assembly, “sponge” sequences as an alignment-guided strategy for reducing artifacts and improving functional genomics analyses.