samplesheet-parser 0.2.1

Format-agnostic parser for Illumina SampleSheet.csv files — supports IEM V1 and BCLConvert V2

samplesheet-parser

Format-agnostic parser for Illumina SampleSheet.csv files.

Supports both the classic IEM V1 format (bcl2fastq era) and the modern BCLConvert V2 format (NovaSeq X series) — with automatic format detection, bidirectional conversion, index validation, Hamming distance checking, diff comparison, and programmatic sheet creation.

SampleSheetFactory auto-detects the format and routes to the correct parser. Both formats share a common interface — SampleSheetConverter handles bidirectional conversion, SampleSheetValidator catches index and adapter issues, SampleSheetDiff compares two sheets across any combination of V1/V2 formats, and SampleSheetWriter builds or edits sheets programmatically.

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The problem this solves

Labs running mixed instrument fleets — older NovaSeq 6000 alongside newer NovaSeq X series — produce two incompatible SampleSheet formats. BCLConvert V2 sheets use [BCLConvert_Settings] / [BCLConvert_Data] sections, OverrideCycles for UMI encoding, and FileFormatVersion in the header. IEM V1 sheets use IEMFileVersion and a flat [Data] section.

Existing tools either hard-code one format or require the caller to know which format they have. samplesheet-parser auto-detects the format, exposes a consistent interface for both, converts between formats, validates index integrity (including Hamming distance), diffs sheets to catch accidental changes before a run starts, and writes new sheets programmatically — so you never have to hand-edit a CSV again.

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Installation

pip install samplesheet-parser

Requires Python 3.10+. No mandatory dependencies beyond loguru.

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Quickstart

Auto-detect format (recommended)

from samplesheet_parser import SampleSheetFactory

factory = SampleSheetFactory()
sheet = factory.create_parser("SampleSheet.csv", parse=True)

print(factory.version)      # SampleSheetVersion.V1 or .V2
print(sheet.index_type())   # "dual", "single", or "none"

for sample in sheet.samples():
    print(sample["sample_id"], sample["index"])

V1 parser directly

from samplesheet_parser import SampleSheetV1

sheet = SampleSheetV1("SampleSheet.csv")
sheet.parse()

print(sheet.experiment_name)   # "MyRun_20240115"
print(sheet.read_lengths)      # [151, 151]
print(sheet.adapters)          # ["CTGTCTCTTATACACATCT"]
print(sheet.index_type())      # "dual"

for sample in sheet.samples():
    print(sample["sample_id"], sample["index"], sample["index2"])

V2 parser + UMI extraction

from samplesheet_parser import SampleSheetV2

sheet = SampleSheetV2("SampleSheet.csv")
sheet.parse()

# OverrideCycles: Y151;I10U9;I10;Y151 → 9 bp UMI in Index1
print(sheet.get_umi_length())       # 9
rs = sheet.get_read_structure()
print(rs.umi_location)              # "index2"
print(rs.read_structure)            # {"read1_template": 151, "index2_length": 10, "index2_umi": 9, ...}

Format conversion

from samplesheet_parser import SampleSheetConverter

# V1 → V2
SampleSheetConverter("SampleSheet_v1.csv").to_v2("SampleSheet_v2.csv")

# V2 → V1  (lossy — V2-only fields are dropped with a warning)
SampleSheetConverter("SampleSheet_v2.csv").to_v1("SampleSheet_v1.csv")

Validation

from samplesheet_parser import SampleSheetFactory, SampleSheetValidator

sheet = SampleSheetFactory().create_parser("SampleSheet.csv", parse=True)
result = SampleSheetValidator().validate(sheet)

print(result.summary())
# PASS — 0 error(s), 2 warning(s)

for w in result.warnings:
    print(w)
# [WARNING] INDEX_DISTANCE_TOO_LOW: Indexes for 'S1' and 'S2' in lane '1'
#   have a Hamming distance of 1 (minimum recommended: 3).
#   This may cause demultiplexing bleed-through.

for err in result.errors:
    print(err)
# [ERROR] DUPLICATE_INDEX: Index 'ATTACTCG+TATAGCCT' appears more than once in lane 1

Diff two sheets

from samplesheet_parser import SampleSheetDiff

diff = SampleSheetDiff("old/SampleSheet.csv", "new/SampleSheet.csv")
result = diff.compare()

print(result.summary())
# Diff (V1 → V2):
#   2 header/settings change(s)
#   1 sample(s) added: SAMPLE_009
#   1 sample(s) with field changes

if result.has_changes:
    for change in result.sample_changes:
        print(change)
    # Sample 'SAMPLE_002' (lane 1):
    #   Index: 'TCCGGAGA' → 'GGGGGGGG'

    for s in result.samples_added:
        print(f"Added: {s['Sample_ID']}")

Works across any combination of V1 and V2 — field names are normalised before comparison so V1-only columns (I7_Index_ID, Sample_Name, etc.) do not generate spurious diffs.

Build or edit a sheet

from samplesheet_parser import SampleSheetWriter
from samplesheet_parser.enums import SampleSheetVersion

# Build a V2 sheet from scratch
writer = SampleSheetWriter(version=SampleSheetVersion.V2)
writer.set_header(run_name="MyRun_20240115", platform="NovaSeqXSeries")
writer.set_reads(read1=151, read2=151, index1=10, index2=10)
writer.set_adapter("CTGTCTCTTATACACATCT")
writer.set_override_cycles("Y151;I10;I10;Y151")
writer.add_sample("SAMPLE_001", index="ATTACTCGAT", index2="TATAGCCTGT", project="Proj")
writer.add_sample("SAMPLE_002", index="TCCGGAGACC", index2="ATAGAGGCAC", project="Proj")
writer.write("SampleSheet.csv")   # validates before writing by default

# Load an existing sheet, edit it, write back
from samplesheet_parser import SampleSheetFactory

sheet = SampleSheetFactory().create_parser("SampleSheet.csv", parse=True)
editor = SampleSheetWriter.from_sheet(sheet)
editor.remove_sample("SAMPLE_005")
editor.update_sample("SAMPLE_002", index="GGGGGGGGGG")
editor.write("SampleSheet_updated.csv")

write() runs SampleSheetValidator before writing by default — pass validate=False to skip. from_sheet(sheet, version=SampleSheetVersion.V1) converts format while editing.

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Format detection logic

The factory uses a three-step detection strategy — no format hints required from the caller:

1. Header discriminator — scan [Header] for FileFormatVersion (→ V2) or IEMFileVersion (→ V1)
2. Section name scan — if no header key found, look for [BCLConvert_Settings] / [BCLConvert_Data] in the full file (→ V2)
3. Default — fall back to V1 (broadest compatibility with legacy files)

The detector reads only as much of the file as needed — stopping after [Header] in the common case.

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Validation checks

Code	Level	Description
EMPTY_SAMPLES	error	No samples in Data section
INVALID_INDEX_CHARS	error	Index contains non-ACGTN characters
INDEX_TOO_LONG	error	Index longer than 24 bp
DUPLICATE_INDEX	error	Two samples share an index in the same lane
DUPLICATE_SAMPLE_ID	error	Same Sample_ID appears twice in one lane
INDEX_TOO_SHORT	warning	Index shorter than 6 bp
INDEX_DISTANCE_TOO_LOW	warning	Two indexes in the same lane have Hamming distance < 3, risking demultiplexing bleed-through
NO_ADAPTERS	warning	No adapter sequences configured
ADAPTER_MISMATCH	warning	Adapter is non-standard

Hamming distance checking

Indexes that are too similar cause read bleed-through between samples during demultiplexing — a common cause of low-quality runs that is not caught by a simple duplicate check. The validator computes the Hamming distance between every pair of indexes within each lane and warns when the distance falls below the recommended minimum of 3.

For dual-index sheets, the I7 and I5 sequences are combined before comparison, so a pair that is close on I7 but well-separated on I5 (as most dual-index kits are designed) is not incorrectly flagged.

# Custom threshold — stricter than the default of 3
from samplesheet_parser.validators import SampleSheetValidator, ValidationResult

samples = sheet.samples()
result = ValidationResult()
SampleSheetValidator()._check_index_distances(samples, result, min_distance=4)

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Diff

SampleSheetDiff compares two sheets — any combination of V1 and V2 — and returns a structured DiffResult across four dimensions:

Dimension	What is compared
Header	Key/value changes in [Header] / [BCLConvert_Settings]
Reads	Read length or cycle count changes
Samples added / removed	Keyed on Sample_ID + Lane
Sample field changes	Per-sample field-level diffs (index, project, etc.)

result = SampleSheetDiff("before.csv", "after.csv").compare()

result.has_changes          # bool
result.summary()            # one-paragraph human-readable summary
result.header_changes       # list[HeaderChange]
result.samples_added        # list[dict]
result.samples_removed      # list[dict]
result.sample_changes       # list[SampleChange]

# Inspect per-sample changes
for sc in result.sample_changes:
    print(sc.sample_id, sc.lane)
    for field, (old, new) in sc.changes.items():
        print(f"  {field}: {old!r} → {new!r}")

V1-only metadata columns (I7_Index_ID, I5_Index_ID, Sample_Name, Description) are suppressed when comparing V1 against V2 so that format differences do not generate noise.

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UMI / OverrideCycles parsing

The V2 OverrideCycles field encodes read structure including UMI positions:

OverrideCycles	UMI length	UMI location
Y151;I10;I10;Y151	0	—
Y151;I10U9;I10;Y151	9	index2
U5Y146;I8;I8;U5Y146	5	read1

sheet.get_umi_length()       # → int
sheet.get_read_structure()   # → ReadStructure dataclass

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API reference

SampleSheetFactory

Method / attribute	Returns	Description
create_parser(path, *, clean, experiment_id, parse)	SampleSheetV1 | SampleSheetV2	Auto-detect format and return appropriate parser
get_umi_length()	int	UMI length from the current parser
.version	SampleSheetVersion	Detected format version

SampleSheetV1 / SampleSheetV2 (shared interface)

Method / attribute	Returns	Description
parse(do_clean=True)	None	Parse all sections
samples()	list[dict]	One record per unique sample
index_type()	str	"dual", "single", or "none"
.adapters	list[str]	Adapter sequences
.experiment_name	str | None	Run/experiment name

V2-only

Method	Returns
get_umi_length()	int
get_read_structure()	ReadStructure

SampleSheetConverter

Method	Returns	Notes
to_v2(output_path)	Path	Converts IEM V1 → BCLConvert V2
to_v1(output_path)	Path	Converts BCLConvert V2 → IEM V1 (lossy)
.source_version	SampleSheetVersion	Auto-detected format of input

SampleSheetValidator

Method	Returns	Description
validate(sheet)	ValidationResult	Run all checks; returns structured result
_check_index_distances(samples, result, min_distance=3)	None	Hamming distance check (callable directly for custom thresholds)

SampleSheetWriter

Method / attribute	Returns	Description
SampleSheetWriter(version=)	—	Instantiate for SampleSheetVersion.V1 or .V2
from_sheet(sheet, version=)	SampleSheetWriter	Load a parsed sheet for editing; optionally change output format
set_header(*, run_name, platform, ...)	self	Set header fields (fluent)
set_reads(*, read1, read2, index1, index2)	self	Set read cycle counts (fluent)
set_adapter(adapter_read1, adapter_read2)	self	Set adapter sequences (fluent)
set_override_cycles(override)	self	Set OverrideCycles string — V2 only (fluent)
set_software_version(version)	self	Set SoftwareVersion — V2 only (fluent)
set_setting(key, value)	self	Set an arbitrary settings key/value (fluent)
add_sample(sample_id, *, index, ...)	self	Append a sample row (fluent)
remove_sample(sample_id, *, lane=)	self	Remove sample(s) by ID, optionally scoped to a lane (fluent)
update_sample(sample_id, *, lane=, **fields)	self	Update fields on an existing sample in-place (fluent)
write(path, *, validate=True)	Path	Serialise to disk; validates first by default
to_string()	str	Serialise to string without writing to disk
.sample_count	int	Number of samples currently in the writer
.sample_ids	list[str]	Sample IDs currently in the writer

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SampleSheetDiff

Method	Returns	Description
compare()	DiffResult	Full comparison across header, reads, settings, and samples

DiffResult

Attribute / method	Type	Description
has_changes	bool	True if any difference was detected
summary()	str	Human-readable one-paragraph summary
header_changes	list[HeaderChange]	Header, reads, and settings diffs
samples_added	list[dict]	Records present in new sheet only
samples_removed	list[dict]	Records present in old sheet only
sample_changes	list[SampleChange]	Per-sample field-level diffs
source_version	SampleSheetVersion	Format of the old sheet
target_version	SampleSheetVersion	Format of the new sheet

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Contributing

git clone https://github.com/chaitanyakasaraneni/samplesheet-parser
cd samplesheet-parser
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Run demo scripts
python scripts/demo_converter.py
python scripts/demo_diff.py
python scripts/demo_writer.py

See CONTRIBUTING.md for the full local testing guide and PR checklist.

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Citation

@software{kasaraneni2026samplesheetparser,
  author  = {Kasaraneni, Chaitanya},
  title   = {samplesheet-parser: Format-agnostic parser for Illumina SampleSheet.csv},
  year    = {2026},
  url     = {https://github.com/chaitanyakasaraneni/samplesheet-parser},
  version = {0.2.0}
}

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License

Apache 2.0 — see LICENSE.

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Related resources

• Illumina IEM V1 SampleSheet reference (Knowledge Article #2204)
• BCLConvert Software Guide
• Upgrading from bcl2fastq to BCLConvert
• Illumina index design recommendations