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Faithfully recapitulate metadata via a round-trip through `writeVcf` + `readVcf`.

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Évaluation

Difficulté
4/5
Temps estimé
3-5 jours
Accessibilité débutants
55/100
Type d'issue
Bug
Clarté
Plutôt claire
Activité
Active
Stack technique
r
Domaine
bioinformatics

Piste de recherche

Commencez par l’exemple reproductible structural.vcf et examinez la gestion des métadonnées par writeVcf/readVcf, en particulier les en-têtes de contig, fileDate et les informations de référence. Utilisez la vérification all.equal du roundtrip comme couverture de régression ; le travail est terminé lorsque les divergences de métadonnées signalées sont résolues sans perdre la provenance prévue.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

writeVcf performs some unnecessary work that interferes with a perfect roundtrip of a VCF to a file and back. At the very least, these discrepancies interfere with my unit tests that check for correct reproduction of a VCF object from a VCF file; they also have some practical consequences as they introduce differences in the MD5 checksums, which then prevents some deduplication mechanisms in backend storage systems. To illustrate:

fl <- system.file("extdata", "structural.vcf", package="VariantAnnotation")
out <- tempfile()
first <- readVcf(fl)
writeVcf(first, out)
roundtrip <- readVcf(out)

all.equal(roundtrip, first)
## [1] "Attributes: < Component “metadata”: Component “header”: Attributes: < Component “header”: Lengths: 9, 8 > >"
## [2] "Attributes: < Component “metadata”: Component “header”: Attributes: < Component “header”: Names: Lengths (9, 8) differ (string compare on first 8) > >"
## [3] "Attributes: < Component “metadata”: Component “header”: Attributes: < Component “header”: Attributes: < Component ## “listData”: Length mismatch: comparison on first 8 components > > >"
## [4] "Attributes: < Component “metadata”: Component “header”: Attributes: < Component “header”: Attributes: < Component “listData”: Component “fileDate”: Attributes: < Component “listData”: Component “Value”: 1 string mismatch > > > >"
## [5] "Attributes: < Component “metadata”: Component “header”: Attributes: < Component “reference”: Lengths (4, 0) differ (string compare on first 0) > >"

For mismatches 1-3: as documented in its manpage, writeVcf adds some ##contig headers based on the seqinfo() of the input object. However, in this case, all the sequence information is NA, so perhaps writeVcf might be smart enough to omit the ##contig headers altogether, rather than manufacturing some non-informative placeholders:

##contig=<ID=1>
##contig=<ID=2>
##contig=<ID=3>
##contig=<ID=4>

For mismatch 4: as documented, writeVcf replaces the fileDate with the current date. Perhaps you could consider an option to respect any existing date in the VCF object, which is useful for retaining provenance, e.g., if I'm using VariantAnnotation to make some changes to an existing VCF file but I want to keep the date of the original file's creation.

For mismatch 5: I'm not sure what happened here, but I'm guessing this has something to do with the extra contig lines.

Session information 
R Under development (unstable) (2023-11-29 r85646)
Platform: aarch64-apple-darwin22.5.0
Running under: macOS Ventura 13.6.1

Matrix products: default
BLAS:   /Users/luna/Software/R/trunk/lib/libRblas.dylib
LAPACK: /Users/luna/Software/R/trunk/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Los_Angeles
tzcode source: internal

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods
[8] base

other attached packages:
 [1] VariantAnnotation_1.49.2    Rsamtools_2.19.2
 [3] Biostrings_2.71.1           XVector_0.43.0
 [5] SummarizedExperiment_1.33.1 Biobase_2.63.0
 [7] GenomicRanges_1.55.1        GenomeInfoDb_1.39.5
 [9] IRanges_2.37.0              S4Vectors_0.41.3
[11] MatrixGenerics_1.15.0       matrixStats_1.2.0
[13] BiocGenerics_0.49.1

loaded via a namespace (and not attached):
 [1] KEGGREST_1.43.0          rjson_0.2.21             lattice_0.22-5
 [4] vctrs_0.6.5              tools_4.4.0              bitops_1.0-7
 [7] generics_0.1.3           curl_5.2.0               parallel_4.4.0
[10] tibble_3.2.1             fansi_1.0.6              AnnotationDbi_1.65.2
[13] RSQLite_2.3.4            blob_1.2.4               pkgconfig_2.0.3
[16] Matrix_1.6-4             BSgenome_1.71.1          dbplyr_2.4.0
[19] lifecycle_1.0.4          GenomeInfoDbData_1.2.11  compiler_4.4.0
[22] stringr_1.5.1            progress_1.2.3           codetools_0.2-19
[25] yaml_2.3.8               RCurl_1.98-1.13          pillar_1.9.0
[28] crayon_1.5.2             BiocParallel_1.37.0      DelayedArray_0.29.0
[31] cachem_1.0.8             abind_1.4-5              tidyselect_1.2.0
[34] digest_0.6.33            stringi_1.8.3            restfulr_0.0.15
[37] dplyr_1.1.4              biomaRt_2.59.0           fastmap_1.1.1
[40] grid_4.4.0               cli_3.6.2                SparseArray_1.3.2
[43] magrittr_2.0.3           S4Arrays_1.3.1           GenomicFeatures_1.55.1
[46] XML_3.99-0.16            utf8_1.2.4               rappdirs_0.3.3
[49] filelock_1.0.3           prettyunits_1.2.0        bit64_4.0.5
[52] httr_1.4.7               bit_4.0.5                png_0.1-8
[55] hms_1.1.3                memoise_2.0.1            BiocIO_1.13.0
[58] BiocFileCache_2.11.1     rtracklayer_1.63.0       rlang_1.1.2
[61] glue_1.6.2               DBI_1.2.0                xml2_1.3.6
[64] R6_2.5.1                 GenomicAlignments_1.39.0 zlibbioc_1.49.0
Langage dominant
R
Étoiles
32
Forks
21
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