How can an international research team translate PLINK 2 genomic-data documentation without breaking the relationship between genotypes, variants and samples? PLINK 2 commonly uses three coordinated files: PGEN for genotype data, PVAR for variant information and PSAM for sample information. Those files form one analytical dataset. The words surrounding them may need translation, but the rows, keys, allele definitions and measurements must continue to mean exactly what the source intended.
Searches for PLINK 2 PGEN PVAR PSAM explained, PLINK files translation, PGEN file format, PVAR REF ALT columns, PSAM FID IID identifiers, PLINK genotype dosage, PLINK 1 BED BIM FAM versus PLINK 2 and VCF-to-PGEN conversion often point to a simple problem: apparently readable column names are actually interfaces between statistical software and evidence. A tidy local-language spreadsheet can become scientifically invalid when someone moves a sample, rewrites an identifier or mistakes a hard call for an imputed dosage.
This practical guide explains the file trio, its relationships, safe multilingual documentation, common conversion hazards, validation exercises and scientific terminology. It is for researchers, scientific editors, data managers, translators, teachers and software teams working across languages. Genetic data may be sensitive personal information: use synthetic examples for teaching and follow approved research access arrangements. Follow the PLINK documentation for your installed build because tool options and format behavior can evolve.
The complete PLINK 2 localization guide
The short answer: translate the explanation, not the genotype
Keep the PGEN, PVAR and PSAM files associated as a matching dataset. Do not rewrite genotype bits, sample IDs, variant IDs, allele strings, coordinate systems or phenotype values just to make the release look local. Localize instructional prose, interface text and approved descriptive metadata in a controlled way. Validate all three files together, because a perfectly readable individual file can still be aligned to the wrong companion file.
The teaching trick is to imagine a three-way join. Genotypes occupy the matrix, variants label one axis and samples label the other. A useful translation helps a reader navigate that join but never changes which biological observation belongs at a particular intersection.
What PLINK is designed to do
PLINK is software for large-scale genetic data handling and analysis, including common association-study operations. PLINK 2 extends earlier formats and can work with several import and export schemes, including VCF and Oxford genotype files. Its preferred PGEN format is not a generic office spreadsheet or a standalone statement about disease.
A local-language guide should distinguish the purpose of a format from the purpose of an analysis. The dataset contains representations of genotypes and related metadata. An association statistic is generated by a defined analytical workflow. Neither the file extension nor the name of a tool by itself supplies a clinical interpretation.
The PGEN-PVAR-PSAM trio
In a standard PLINK 2 fileset, .pgen contains encoded genotype data, .pvar carries variant metadata and .psam describes samples. Names should share the intended base and be loaded together using the appropriate command interface. A mismatch in row or column membership can yield a failure to load or, in poorly managed downstream transformations, an incorrect mapping.
For teaching, use a toy dataset of three people and four variants. Put sample labels in PSAM and variant labels in PVAR, then draw a matrix for PGEN. Even readers who have never used the program can see why the separate dimensions must agree and why those files should be transferred as a controlled set.
PGEN is not a human-readable genotype report
PGEN is a binary format optimized for genotype representation and efficient processing. PLINK 2 can preserve hard calls, dosage information and certain phase-related information depending on the source and operation. A generic text editor cannot safely translate a binary stream; even if it displays fragments resembling words, those fragments do not define its structure.
Use a documented PLINK command or a compatible library to inspect the intended data. If a bilingual help page requires an illustration, create a decoded synthetic table and label it as a representation. Do not imply that each screen cell is stored in PGEN as the same printable characters.
PVAR defines the variant axis
A PVAR file resembles a VCF-style variant information table. Common core columns include chromosome, base-pair position, variant ID, reference allele and alternate allele or alleles. Additional columns may contain quality, filtering, information or other fields, depending on the imported dataset and output options.
The record’s labels are not just prose headings. They specify how rows are interpreted by software and help join variant records with external references. Keep field names such as #CHROM, POS, ID, REF and ALT in the canonical machine-readable output, even if the educational explanation translates their meanings.
PSAM defines the sample axis
PSAM identifies samples and may record fields such as individual or family identifiers, sex, parental IDs and phenotype data. The exact available columns depend on the fileset and command options. A person who sees an IID may understandably call it a name, but it is a key, not a greeting or a translated personal label.
In an approved anonymized exercise, use generated sample IDs such as DEMO001 and DEMO002. Leave those keys unchanged across languages. If a human-facing guide must discuss what a sample represents, place the explanation in a separate description field rather than inside the identifiers that calculations rely on.
The leading hash in a header matters
PLINK-generated text tables commonly use a header line beginning with #. In PVAR, #CHROM introduces the variant-column header under the documented convention. In PSAM, labels such as #IID can identify the sample-table structure. A translation that removes a marker as if it were decoration may make a file fail to parse.
A safe bilingual handbook quotes technical header strings exactly in a code-styled block and translates their definitions immediately below. When examples are copyable, test them with the intended PLINK reader. A page can use a localized heading outside the example without changing a single byte of the sample file.
FID and IID are not synonyms
The family ID and within-family individual ID serve different roles where those columns are used. Some workflows operate with an individual-only identity convention, while others represent family structure. Replacing the two columns with one human-friendly ‘participant’ label can destroy information or create ambiguous joins.
Teach the key convention used by the particular fileset. If two families have an IID with the same visible value, a family-aware key can disambiguate them. If a tool or project uses a different requirement, document it explicitly rather than making assumptions based on a toy spreadsheet.
Sample order must survive every transfer
Binary genotype entries are linked to sample metadata by the format’s defined ordering. Re-sorting a PSAM table alphabetically while keeping PGEN unchanged is not a harmless cosmetic change. It can associate one person’s genotype with another person’s phenotype in tools or pipelines that assume positional correspondence.
A translation workflow should keep any decoded table and the original sample-order mapping together. For a spot check, choose several sample IDs, compare their genotype or dosage values before and after export, and verify the same row-to-person relationship. Pass the entire fileset through a trusted reader as well.
Variant order is equally important
PVAR carries variant records corresponding to the PGEN variant dimension. Sorting genomic coordinates, renaming IDs or trimming duplicate-looking rows cannot be carried out independently on just the text table. A file that still looks structurally valid may no longer describe the binary genotype records as intended.
When a researcher requests a neatly ordered translated report, generate that report from a format-aware query or conversion. Do not sort the underlying PVAR in isolation. Record whether a legitimate computational transformation created a new PGEN and PVAR pair, and keep the original files intact for audit.
Reference alleles and alternate alleles
REF is the reference allele in the relevant convention, while ALT denotes alternative allele information. Their roles are not decided by which base letter looks alphabetically first. Some imported data contain provisional reference assignments; PLINK documentation describes how such status is represented and handled.
A translation that switches REF and ALT while retaining the underlying genotype counts or dosages can reverse interpretation. To demonstrate, explain an A-reference/G-alternate variant and a dosage of G. If an approved computational transformation swaps alleles, it must also update all dependent representations and document the change.
Why provisional reference status matters
An imported dataset may not consistently identify true reference alleles. PLINK 2 can represent provisional reference status and recognizes a related INFO flag convention. Calling a provisional assignment ‘the confirmed reference genome base’ in a multilingual guide overstates the source data.
A careful explanation separates the actual letter stored in REF from the evidence supporting its reference status. When the chosen genome assembly is known, state it. If status is provisional, use a faithful translation of that uncertainty. Do not silently upgrade a tentative reference assignment into an authoritative biological claim.
Coordinate systems and genome assemblies
Variant positions must be read relative to their declared chromosome and reference assembly. Numbers that look unambiguous may correspond to different physical loci under different genome builds. Translating an assembly name or changing a chromosome label to match a local-language convention can break lookup and comparison.
In a variant-data dictionary, show CHROM, POS, REF, ALT and assembly in one coherent entry. A publication can explain what a genomic assembly is using plain language, but its canonical identifier should remain intact. Record any actual liftover as a documented data transformation, never as an editorial spelling correction.
Hard calls versus dosages
A hard call expresses a discrete genotype assignment, typically as allele counts or categories. A dosage is an expected allele count that may be fractional because imputation probabilities are uncertain. PLINK 2 supports dosage-aware operations, and commands differ in whether they use dosages or require hard calls.
Imagine a dosage of 0.8 for a specified allele. It is not a claim that the sample has eight tenths of a physical allele. It summarizes probabilistic evidence. A translated teaching paragraph should explain the distinction before anyone compares an imputed dosage column with a hardcall-only result.
A dosage does not retain every probability
Different combinations of genotype-state probabilities can yield the same expected dosage. That means a pipeline importing full probabilities and storing a dosage may not preserve all the detail needed to reconstruct the original distribution. This is a mathematical limitation of a summary statistic, not a spelling issue.
When writing a BGEN-to-PGEN conversion guide, say which fields survive and what is summarized. A good validation example compares expected allele counts and missingness, then makes clear that equality of dosages does not prove equality of the original probability vectors.
Hard-call thresholds are analysis choices
PLINK 2 provides command options that influence when imported dosage information yields a hard call or missing assignment. Such thresholds are part of data-processing policy and can change results. They should be recorded as exact numeric options rather than paraphrased into reassuring words like ‘strict’ or ‘lenient.’
For a training example, compare two analyses with different specified thresholds and show why their hard-call counts may differ. Retain the source command line and output statistics. In translation, explain the implication of the choice without modifying the threshold or claiming it is universal for all studies.
Missing genotypes are not negative findings
A sample may have no genotype call at a variant or lack dosage information. Missingness must be handled according to the file and analysis conventions, not recoded into a visible zero because the local language lacks a convenient abbreviation. Zero counted copies is a legitimate value distinct from unknown information.
A multilingual report should include a specific display label for missing and explain how it differs from zero. Before an analyst shares a localized plot, compare missing data counts in the source and output. A newly reduced missingness rate without a documented transformation is a warning sign.
PLINK 1 BED, BIM and FAM versus PLINK 2
PLINK 1 commonly uses a BED binary genotype file with companion BIM and FAM text files. PLINK 2’s PGEN, PVAR and PSAM scheme supports additional functionality. Both are important historically, and PLINK can support certain mixed or compatible loading modes. Their names should not be treated as interchangeable just because all six files concern genetics.
State exactly which command expects which files. A tutorial may compare BED/BIM/FAM with PGEN/PVAR/PSAM, but each example should declare its chosen mode. If the script calls –pfile while the reader copied files from a –bfile example, the problem is a command-and-format mismatch, not a failure of translated language.
Do not confuse PLINK BED with genomic-interval BED
The extension .bed can refer to the PLINK 1 binary biallelic genotype table or to a completely different human-readable genomic-interval format often used in genome browsers. This is an exceptionally easy collision in search results and translated glossaries. The same extension does not establish the same schema.
Always qualify it as ‘PLINK BED binary genotype’ or ‘UCSC-style BED interval’ depending on context. Show the expected companion files and parser. An editor who publishes ‘open every BED in a text editor’ could mislead readers working with PLINK binary data.
PVAR can carry VCF-style metadata
The PVAR format can include recognizable VCF-like metadata elements such as information-field declarations, chromosome-set context or additional variant-level columns. Those directives affect how subsequent columns are interpreted. A translator who deletes lines beginning with double hashes as visual clutter may remove important semantics.
Teach readers that a machine-readable declaration and an informal comment are not necessarily the same. Quote actual header lines in preserved form, describe their meaning alongside them and test the resulting file with the target application. If the dataset defines custom INFO keys, consult that dataset’s dictionary before translating descriptions.
Sex and phenotype fields need careful interpretation
A sample table may contain sex codes and one or more phenotype columns, but the coding schemes and missing-value conventions depend on project and command settings. Sex codes in files are not a substitute for nuanced human identity language. A case/control phenotype should not be translated into a medical diagnosis unsupported by the study.
Explain the defined scientific variable with its context, type and permitted values. Keep the encoded value unchanged in machine input, then provide a humane, accurate display explanation for readers. For sensitive attributes, limit exposure and follow institutional review and applicable law.
Covariates and phenotype data do not belong in a guess
Many association workflows combine genotype data with external phenotype and covariate files. These may encode age, batch, ancestry-related adjustments or other variables with exact column names and missing-data rules. The scientific meaning of an analysis can change if those labels are localized inside the executable input without updating the script.
A multilingual training manual should present the real source column name, its translated explanation, units and permitted values. For a numerical variable, say whether a threshold is inclusive and what measurement units apply. If localization requires different display labels, keep a stable mapping back to the canonical analytical field.
Compressed text companions and file suffixes
Depending on the supported commands and environment, PLINK tools may accept compressed forms of variant or other text data. A suffix such as .zst indicates an encoding layer, not a new biological concept. A reader who treats a compressed PVAR as plain text will see unreadable bytes or an error.
Document the exact filename and supported reader behavior used in the workflow. Never advise readers to change a file extension alone to force compatibility. Decompress through appropriate tooling and verify that the recovered structure matches the documented input format before any linguistic work begins.
Embedded and external PGEN indexes
Many PGEN files have an embedded index. In a supported configuration where an external .pgen.pgi index is used, its relationship to the binary genotype file must remain intact. The index supports access to records; it is not an independent description of variants or samples.
A translation project should keep file components and companion artifacts associated in the release manifest. If a binary or its index is regenerated by software, log the tool version and test access to representative variants. A missing index error should not be explained to readers as an absent biological observation.
How to construct an honest format comparison
A useful comparison table has columns for file purpose, typical content, human readability, join axis and safe localization action. PGEN is binary genotype data; PVAR is variant metadata; PSAM is sample metadata. Related VCF, BGEN and old PLINK formats appear in a separate group with qualified differences.
This helps readers decide whether they need a translator, a parser, a data-conversion command or a scientific analyst. The table should not promise that converting between formats is lossless under every option. Whenever fields are dropped, transformed or inferred, state it in the comparison note.
Names, IDs and Unicode boundaries
Sample and variant IDs may contain punctuation or unusual characters. Their intended representation depends on the specific tool and source conventions. A font may change how a character appears, while normalization or substituting visually similar letters can change the exact key used for joins.
In a multilingual interface, present a decoded display label next to the immutable identifier where permitted. Avoid translating rsIDs, contig IDs and software option names. In test data, include an identifier with an underscore and one with a hyphen to confirm that the documentation never implies punctuation can be casually removed.
A correct load is necessary but not sufficient
If PLINK successfully loads the fileset, you know the input is compatible enough for that operation. You do not yet know that every source relationship survived a preceding localization or conversion step. Software can accept a coherent but wrongly matched sample table after someone changes the inputs together.
Build a stronger verification layer: compare sample counts, variant counts, key sets, a few known genotype or dosage values, allele mapping, frequency summaries and missingness. Include the original and new command arguments. A valid output should be reproducible and scientifically comparable to the declared source.
A practical safe conversion workflow
First preserve the original fileset and record its checksums and provenance. Then select a format-aware importer and specify the exact genome reference and allele conventions. Run the conversion and inspect generated logs, warnings, sample counts and variant counts. Only after scientific checks pass should the team localize explanatory documents and interfaces.
This order keeps conversion errors from being mistaken for translation errors. Provide users with a clean source-to-output mapping and a record of intentional transformations. If a target tool discards phase or probabilities, say so openly; do not hide material losses beneath a general claim of interoperability.
Multilingual quality assurance has two independent passes
The first pass checks machine relationships, values and metadata. The second reviews scientific meaning expressed in human language. A specialist may confirm that REF, ALT, dosage, case/control and missingness are faithfully explained; a native-language editor may make the result readable without relaxing those definitions.
Neither pass replaces the other. A fluent translation can be scientifically misleading, and a structurally correct fileset can be surrounded by incomprehensible instructions. Keep reviewers’ comments distinct so changes to an explanatory heading cannot accidentally become edits to the source genotype data.
Privacy is part of data localization
Even pseudonymized genetic data may allow sensitive inferences and can be subject to strict permissions. Translation work usually does not require a copy of a real cohort’s genotype matrix. Give translators field definitions, synthetic examples and approved language strings wherever possible.
The public teaching version should never expose real person IDs, clinical phenotypes or identifiable pedigree information. If a secure review genuinely requires access to restricted data, use an approved environment and document the legal and institutional authority for that access. Linguistic improvement is not an exception to research safeguards.
Prepare a controlled release manifest
A useful manifest records the precise filenames, whether the trio matches, file checksums, format-related software version, genome assembly, field dictionaries, localization languages, review dates and validation commands. It also lists what was translated and what remained byte-identical.
This document gives the next team enough context to reproduce a result rather than merely admire a translated screenshot. Where a format conversion was performed, label the output as a derived dataset and note any losses. Where only the documentation was localized, make clear that the source analytical files did not change.
Explain association results without false certainty
A PLINK workflow can produce association statistics, quality-control measures and intermediate representations. None of these automatically establishes medical causation. A variant that correlates with a phenotype under a model may be affected by sampling, confounding or other limitations.
A world-facing article should not turn a p-value into the probability that an individual has a condition. It should state the statistical question and underlying assumptions clearly. Translators safeguard the scientific distinction by checking units, confidence-interval language, threshold descriptions and the wording of conclusions.
When the documentation and command disagree
Sometimes a help page describes a command as dosage-aware, but an actual command or downstream operation uses hard calls. Sometimes an example says PVAR but the file is BIM. Do not resolve the conflict by choosing whichever version is easier to translate.
Read the installed PLINK documentation, logs and sample output; identify the exact operation and its input expectations; then update the explanatory draft to match verified behavior. Keep any unresolved uncertainty visible. A language team should not quietly redefine scientific behavior to make the narrative smoother.
Twelve realistic repair cases
A translated sample table is sorted independently
A coordinator alphabetizes participant IDs in the local-language PSAM export but keeps the PGEN matrix unchanged. The counts still match, yet row correspondence is broken. The correction is to restore the source ordering or regenerate all related files with a documented, format-aware transformation. Spot-checking several genotype values against known IDs is the only convincing demonstration that the intended alignment survived.
A reference allele is mistaken for the common allele
An editor explains REF as ‘the most common allele’ because that phrase seems accessible. But reference and most-common are not synonyms. The translated tutorial must define REF according to the reference convention and separately explain allele frequency. If the source assignment is provisional, the handbook needs to state that limitation rather than assuming the reference letter is certain.
A dosage is reported as a hard call
A research summary rounds every expected dosage to an integer and describes the result as a measured genotype. The original data contained fractional imputation estimates. The safe report distinguishes original dosage, derived hard call and threshold, and states which figure was used in each analysis. Rounding for display must not silently become a new analysis rule.
PLINK BED opens as unreadable symbols
Someone searches for ‘BED format explained’ and finds a genomic-interval text tutorial. They attempt to apply it to PLINK’s binary .bed, mistaking the unreadable output for corruption. The solution is to distinguish the unrelated formats by context and companion files. A PLINK genotype BED belongs with BIM and FAM, not a BED interval browser import.
A PVAR column changes name in a CSV
A translator replaces #CHROM with a localized word and saves the PVAR data as a comma-separated spreadsheet. The target parser no longer recognizes the header, and the delimiter convention has changed. For software input, restore the machine-readable header and supported delimiter rules. Put translated explanations in a separate companion document or user interface.
The genome build is omitted
A variant example gives chromosome and position but no genome assembly. A collaborating lab compares the location against a different build and questions the result. The guide should record the authoritative build and coordinate convention. If unknown, it must say unknown. Supplying an attractive but invented assembly label is worse than documenting a gap.
A phenotype code becomes a diagnosis
A PSAM phenotype has a numeric case/control code according to a particular study. A public translation presents one code as a clinically confirmed diagnosis. The appropriate guide describes the variable’s original research definition and any ascertainment limitations. It should not infer medical status from a data dictionary entry that does not support such a claim.
A missing call becomes an allele count of zero
An analyst exports a user-friendly table and replaces missing values with 0 to prevent empty-looking cells. That changes denominators and can alter downstream calculations. Use explicit missing markers according to the target format, preserve zero as a legitimate count and compare missingness statistics before and after the export.
A PGEN conversion hides lost detail
A team converts from BGEN probabilities to a PLINK representation and tells readers the files are identical because their dosages match. Different genotype probability distributions may produce the same dosage. The honest report specifies which information is retained and what has been summarized, and validates the output for the intended statistical workflow.
The same IID occurs in two families
A bilingual personnel table removes FID and keeps only IID because ‘family’ sounds irrelevant. Two samples now appear to have the same identifier. Preserve the key structure required by the dataset and tool; describe the difference in accessible language. Any sanctioned pseudonymization should happen under an approved, reversible mapping rather than ad hoc editing.
The example’s command options change across editions
A translated manual copies an option from a different software build, and the installed PLINK rejects the command. The correct response is to confirm the version and the supported command syntax, revise the educational example and include the version in the source note. A translation should not claim a universal command line when behavior is documented as version-dependent.
A safe public learning exercise
An educator creates synthetic PGEN/PVAR/PSAM teaching data with three fictitious samples. Students localize descriptions, compute a simple allele count, identify missing values and run a documented validation command. No participant data or confidential phenotype is exposed. The exercise communicates both scientific meaning and good research discipline.
A field-level quality-assurance checklist
- Record the exact PLINK tool version.
- Confirm the PGEN, PVAR and PSAM files share the correct dataset identity.
- Verify sample count and variant count.
- Check the machine-readable PVAR headers.
- Check the machine-readable PSAM headers.
- Preserve FID and IID semantics.
- Preserve genotype-to-sample positional mapping.
- Preserve variant-to-genotype positional mapping.
- Record the genome assembly.
- Keep REF and ALT assignments or document an approved transformation.
- Distinguish hard calls, dosages and source probabilities.
- Check missing values separately from numerical zeros.
- Compare representative genotype values across conversions.
- Review phenotype type, coding and units.
- Document command options and logs.
- Inspect provisional reference status.
- Distinguish PLINK BED from genomic interval BED.
- Confirm external index behavior when used.
- Keep private data in approved environments.
- Attach a bilingual data dictionary and release manifest.
Questions readers ask before converting PLINK files
What is the difference between PGEN and PVAR?
PGEN is the binary genotype data; PVAR describes variants and allele context. They are companion components of a PLINK 2 fileset, not alternate spellings of the same information.
What does PSAM contain?
It identifies samples and can include sample metadata or phenotypes under defined conventions. Its relationship to the genotype matrix must remain intact.
Can I translate column headers in PVAR or PSAM?
Keep machine-readable headers exactly as required for executable input. Translate their definitions in a separate data dictionary or display interface.
Is a dosage a disease-risk percentage?
No. It is typically an expected count for a defined allele, not a clinical risk probability. Interpreting it requires the variant context and analysis assumptions.
Why do REF and ALT need care?
Genotype and dosage interpretation can depend on which allele is counted and how reference status is represented. Reordering allele labels without a valid transformation can invert meaning.
Can PLINK read old BED/BIM/FAM datasets?
PLINK 2 supports old-style PLINK inputs and certain compatible modes. Check the documented loading command and do not confuse PLINK BED with genome-browser BED intervals.
How should I translate missing?
As missing or unavailable genotype information in the applicable context, not as a confident zero or a negative diagnosis.
What must I validate after conversion?
Check counts, sample keys, variant keys, allele conventions, dosage or call values, missingness and logs. Explicitly document any loss of probability or phase detail.
Can I share a translated dataset publicly?
Only when the source data’s consent, governance and legal terms permit release. Prefer synthetic data for education and translate documentation without exporting private genotypes.
Does successful loading prove the science is right?
No. It proves that the file was accepted for that operation. Verify provenance, semantics, key alignment and representative values independently.
The final principle
A research dataset is a relationship among people or samples, genomic positions, allele definitions and encoded observations. Translation makes that relationship understandable to new readers; it must not silently change it. Preserve identifiers, source values and computational assumptions. Produce helpful target-language explanations with a parallel vocabulary that can always be traced back to the machine-readable keys.
If a workflow must transform the data, make that a separate, documented computational step with its own checks. If the task is only localization, the stronger outcome is often an unchanged analytical fileset and an exceptionally clear multilingual handbook. Reproducibility, participant privacy, technical compatibility and understandable prose can coexist when their boundaries are explicitly managed.
Additional hands-on numerical and language exercises
Practice: check a three-file identity before reading values
Create a synthetic PLINK 2 fileset with two sample IDs and three variants. Write the expected dimensions in a separate manifest and load the files with the documented command. Now imagine replacing only the PSAM with a different file that has the same number of rows. Row counts may still agree, yet the sample identities can be wrong. The review must compare stable keys and representative genotype values against the intended source, not merely check whether software prints a successful-load message. This is why PGEN, PVAR and PSAM should be treated as one scientific release unit even though they are stored as separate files.
Practice: calculate a dosage and identify lost information
For a synthetic biallelic diploid case, let the genotype probabilities for zero, one and two alternate copies be 0.10, 0.40 and 0.50. The expected alternate dosage is 0 times 0.10 plus one times 0.40 plus two times 0.50, or 1.40. Another probability vector can produce the same 1.40 without being identical to the first. A PGEN description may correctly explain dosage preservation while also stating that it does not automatically recover every source genotype probability. Students should be asked to distinguish a statistic’s numerical equivalence from full informational equivalence.
Practice: preserve REF and ALT when making a graph
An analyst creates a bar chart for the frequency of the G alternate allele at an A-reference/G-alternate variant. A multilingual editor reorders the label as G/A because it is easier to read locally. If the underlying dosage still refers to G, a chart should state that explicitly, rather than suggesting the counted allele changed. The reader should see the variant ID, reference allele, alternate allele, counted allele and assembly where known. A useful caption defines why the frequency was computed and what samples are included. This prevents a simple label change from becoming a scientific sign error.
Practice: distinguish a missing phenotype from a control
A PSAM example contains a study phenotype with control, case and missing categories. A spreadsheet transformation replaces blank cells with zero to make the table visually complete. If the study uses zero for controls, missing participants now become false controls, changing denominators and potentially changing an association analysis. The safe guide uses the missing-value convention specified by the workflow, keeps it distinct from control status and tests category counts after any export. The translation should not turn an administrative absence of information into a negative biological finding.
Practice: explain provisional reference status
Two source files contain the same variant locus but differ in the confidence of their REF assignment. One dataset follows a reference assembly explicitly; another marks reference alleles as provisional after an import that did not fully establish the orientation. A bilingual guide should not erase that difference by calling both ‘confirmed reference base.’ Keep any provisional flag or documented status intact and teach the conditions under which it can be resolved. A scientific reviewer should determine whether an actual harmonization step occurred before approving a stronger target-language description.
Practice: prevent PLINK BED and genomic BED confusion
Write two filenames on the board: example.bed accompanied by example.bim and example.fam, and intervals.bed accompanied by a genome-browser interval description. They share an extension but not the same representation. Ask students which parser should open each and which information each can hold. A successful explanation identifies the PLINK file as binary genotype data and the interval file as coordinates or genomic regions. This disambiguation is essential in search-facing translated material because the shorter phrase ‘BED file’ attracts users with two completely different needs.
Practice: preserve donor and family identity semantics
A demonstration PSAM has a family-aware key FID plus IID. Two individuals share an IID string inside different families, so the pair is needed under the chosen convention. A translator drops FID and calls IID a universal participant identifier. The join is no longer unique. The repaired tutorial shows why an identifier can be locally unique but not globally unique and explains the project’s actual composite-key rule. If identity conventions differ by dataset, state the difference. Do not infer or reveal real family relationships from production data for the sake of an educational figure.
Practice: test conversion as a separate computation
Take a small synthetic VCF with known sample IDs, allele labels and genotype fields. Import it into PLINK 2 using the documented options, record the log and inspect the resulting PGEN/PVAR/PSAM dimensions, missingness and representative genotype data. The target-language manual should explain what that command does and which information survives. If an input field is dropped or a dosage rule changes its interpretation, name the loss explicitly. This is an analysis verification exercise, not a translation adjustment, and preserving the original VCF allows a future reader to reproduce the distinction.
Practice: build a reproducibility report
A complete handoff can include the original filenames and checksums, software version, command options, genome build, sample and variant counts, allele-orientation notes, phenotype dictionary and bilingual terminology table. Add a small set of verified row-level examples whose values readers can reproduce with synthetic data. Record what was translated and which machine-facing identifiers were left unchanged. Finally, ask two independent reviewers to sign off on different questions: does the explanation read correctly in the target language, and does the analytical object retain the same interpretation as its source? Neither judgment alone is sufficient.
Primary references and related guides
- PLINK 2 official file-format reference — PGEN, PVAR, PSAM and legacy formats.
- PLINK 2 documentation and release information — commands and supported analysis features.
- Translate Like a Pro: BGEN genotype probabilities — source distributions and imputation.
- Translate Like a Pro: VCF 4.5 and BCF — related variant representation.