3′ Adapter Readthrough

Real Illumina libraries whose insert is shorter than the read length “read through” the fragment into the 3′ sequencing adapter — the read’s tail is adapter sequence, not genome. eidolon can simulate this so short-insert data looks realistic and exercises downstream adapter-trimming QC. Disabled by default — output is byte-identical to prior versions when the adapters block is omitted.

adapters:
  enabled: true
  preset: truseq        # truseq | nextera | custom
  # for preset: custom, give explicit 5′→3′ uppercase-ACGT sequences:
  # r1: AGATCGGAAGAGC...
  # r2: AGATCGGAAGAGC...

When enabled, any fragment whose insert is shorter than read_len is kept (instead of being resampled away) and the read is padded to read_len at its 3′ end with adapter sequence — R1 gets r1, R2 gets r2 (appended after R2 is reverse-complemented, matching real read orientation). Adapter bases carry the same quality/error models as genomic bases, are marked soft-clipped (S) in the golden BAM, and never introduce variants. How much readthrough you get is controlled by how many inserts fall below read_len — i.e. by fragment_mean / fragment_st_dev relative to read_len. With a long-insert setting (fragment_mean ≫ read_len) essentially no reads reach the adapter and enabling this changes nothing.

Presets:

• truseq — Illumina TruSeq (AGATCGGAAGAGC…), the most common.
• nextera — Nextera / transposase (CTGTCTCTTATACACATCT).
• custom — supply your own r1 / r2.

Not compatible with long_reads: true (adapter readthrough is a short-read phenomenon).

When to enable it

• Validating adapter-trimming pipelines — generate reads with known adapter content to confirm fastp / cutadapt / Trim Galore settings actually detect and remove it.
• Short-insert libraries — small-RNA / cfDNA / degraded-DNA style data where inserts sit near or below the read length and readthrough is expected; the simulated reads then match what the sequencer really produces.
• Aligner soft-clip benchmarking — untrimmed adapter tails should be soft-clipped by the aligner; use this to check that behaviour end-to-end.
• Realistic FASTQ→VCF tests — exercise the whole trim → align → call path on data that carries adapters instead of idealized adapter-free reads.

To keep short inserts as genomic reads without modeling adapters (e.g. to study the coverage behaviour of a short-insert library on its own), set keep_short_fragments: true instead of enabling adapters — short fragments are then emitted as insert-length reads with no adapter padding.

Validated behaviour (paired germline benchmark: chr22, 30×, TruSeq, 3 reps/arm, BWA-MEM2 → GATK HaplotypeCaller vs the golden VCF): adapter readthrough is detectable (fastp adapter content and aligner soft-clip fraction rise only when it is enabled) and fully callable — SNP and indel recall/precision/F1 are unchanged within replication noise whether the adapters are fastp-trimmed or left for BWA-MEM2 to soft-clip. An adapter-free short-insert control showed the only fidelity difference versus a long-insert baseline is the reduced effective coverage of short inserts (mate overlap), not the adapters.