A package for importing common bioinformatic file formats into R as tibbles.
You can install and update importbio using the remotes package. Use
the install_github() function to install the package.
install.packages("remotes")
remotes::install_github('davetang/importbio')Use the update_packages() function to update the package. You can
check the version using the packageVersion() base function.
remotes::update_packages("importbio")
packageVersion("importbio")Import a VCF file.
importvcf(system.file("extdata", "Pfeiffer.vcf.gz", package = "importbio"))
#> # A tibble: 101 × 12
#> vid CHROM POS ID REF ALT QUAL FILTER INFO FORMAT manuel type
#> <chr> <fct> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <fct>
#> 1 1_8665… 1 866511 rs60… C CCCCT 258.… PASS AC=2… GT:AD… 1/1:6… ins
#> 2 1_8793… 1 879317 rs75… C T 150.… PASS AC=1… GT:AD… 0/1:1… snv
#> 3 1_8794… 1 879482 . G C 484.… PASS AC=1… GT:AD… 0/1:2… snv
#> 4 1_8803… 1 880390 rs37… C A 288.… PASS AC=1… GT:AD… 0/1:1… snv
#> 5 1_8816… 1 881627 rs22… G A 486.… PASS AC=1… GT:AD… 0/1:1… snv
#> 6 1_8840… 1 884091 rs75… C G 65.46 PASS AC=1… GT:AD… 0/1:6… snv
#> 7 1_8841… 1 884101 rs49… A C 85.81 PASS AC=1… GT:AD… 0/1:6… snv
#> 8 1_8924… 1 892460 rs41… G C 1736… PASS AC=1… GT:AD… 0/1:8… snv
#> 9 1_8977… 1 897730 rs75… C T 225.… PASS AC=1… GT:AD… 0/1:1… snv
#> 10 1_9092… 1 909238 rs38… G C 247.… PASS AC=1… GT:AD… 0/1:9… snv
#> # ℹ 91 more rowsImport a BED file.
importbed(system.file("extdata", "refseq.bed.gz", package = "importbio"))
#> # A tibble: 101 × 12
#> chrom chromStart chromEnd name score strand thickStart thickEnd itemRgb
#> <fct> <int> <int> <chr> <chr> <chr> <int> <int> <chr>
#> 1 chr1 67092164 67134970 NM_001276… 0 - 67093579 67127240 0
#> 2 chr1 67092164 67134970 NM_001276… 0 - 67093004 67127240 0
#> 3 chr1 67092164 67134970 NR_075077… 0 - 67134970 67134970 0
#> 4 chr1 67092175 67109072 XM_011541… 0 - 67093004 67103382 0
#> 5 chr1 67092175 67131183 XM_011541… 0 - 67093004 67127240 0
#> 6 chr1 67092175 67131227 XM_017001… 0 - 67093004 67127240 0
#> 7 chr1 67092175 67134962 XM_011541… 0 - 67093004 67127240 0
#> 8 chr1 67092175 67141646 XM_011541… 0 - 67093004 67127240 0
#> 9 chr1 67093484 67131227 XM_017001… 0 - 67093569 67127240 0
#> 10 chr1 67093484 67131227 XM_011541… 0 - 67093579 67127240 0
#> # ℹ 91 more rows
#> # ℹ 3 more variables: blockCount <int>, blockSizes <chr>, blockStarts <chr>Import a GTF file.
importgtf(system.file("extdata", "gencode.v38.annotation.sample.gtf.gz", package = "importbio"))
#> # A tibble: 94 × 24
#> seqname source feature start end score strand frame gene_id gene_type
#> <fct> <chr> <chr> <int> <int> <chr> <chr> <chr> <list> <list>
#> 1 chr1 HAVANA gene 11869 14409 . + . <chr [1]> <chr [1]>
#> 2 chr1 HAVANA transcript 11869 14409 . + . <chr [1]> <chr [1]>
#> 3 chr1 HAVANA exon 11869 12227 . + . <chr [1]> <chr [1]>
#> 4 chr1 HAVANA exon 12613 12721 . + . <chr [1]> <chr [1]>
#> 5 chr1 HAVANA exon 13221 14409 . + . <chr [1]> <chr [1]>
#> 6 chr1 HAVANA transcript 12010 13670 . + . <chr [1]> <chr [1]>
#> 7 chr1 HAVANA exon 12010 12057 . + . <chr [1]> <chr [1]>
#> 8 chr1 HAVANA exon 12179 12227 . + . <chr [1]> <chr [1]>
#> 9 chr1 HAVANA exon 12613 12697 . + . <chr [1]> <chr [1]>
#> 10 chr1 HAVANA exon 12975 13052 . + . <chr [1]> <chr [1]>
#> # ℹ 84 more rows
#> # ℹ 14 more variables: gene_name <list>, level <list>, hgnc_id <list>,
#> # havana_gene <list>, transcript_id <list>, transcript_type <list>,
#> # transcript_name <list>, transcript_support_level <list>, tag <list>,
#> # havana_transcript <list>, exon_number <list>, exon_id <list>, ont <list>,
#> # protein_id <list>Import a GTF file but keeping only the gene features.
importgtf(system.file("extdata", "gencode.v38.annotation.sample.gtf.gz", package = "importbio"), keep_feature = "gene")
#> # A tibble: 11 × 15
#> seqname source feature start end score strand frame gene_id gene_type
#> <fct> <chr> <chr> <int> <int> <chr> <chr> <chr> <list> <list>
#> 1 chr1 HAVANA gene 11869 14409 . + . <chr [1]> <chr [1]>
#> 2 chr1 HAVANA gene 14404 29570 . - . <chr [1]> <chr [1]>
#> 3 chr1 ENSEMBL gene 17369 17436 . - . <chr [1]> <chr [1]>
#> 4 chr1 HAVANA gene 29554 31109 . + . <chr [1]> <chr [1]>
#> 5 chr1 ENSEMBL gene 30366 30503 . + . <chr [1]> <chr [1]>
#> 6 chr1 HAVANA gene 34554 36081 . - . <chr [1]> <chr [1]>
#> 7 chr1 HAVANA gene 52473 53312 . + . <chr [1]> <chr [1]>
#> 8 chr1 HAVANA gene 57598 64116 . + . <chr [1]> <chr [1]>
#> 9 chr1 HAVANA gene 65419 71585 . + . <chr [1]> <chr [1]>
#> 10 chr1 HAVANA gene 89295 133723 . - . <chr [1]> <chr [1]>
#> 11 chr1 HAVANA gene 89551 91105 . - . <chr [1]> <chr [1]>
#> # ℹ 5 more variables: gene_name <list>, level <list>, hgnc_id <list>,
#> # havana_gene <list>, tag <list>Import a GFF3 file.
importgff(system.file("extdata", "gencode.v38.annotation.sample.gff3.gz", package = "importbio"))
#> # A tibble: 92 × 26
#> seqname source feature start end score strand frame ID gene_id gene_type
#> <fct> <chr> <chr> <int> <int> <chr> <chr> <chr> <lis> <list> <list>
#> 1 chr1 HAVANA gene 11869 14409 . + . <chr> <chr> <chr [1]>
#> 2 chr1 HAVANA transc… 11869 14409 . + . <chr> <chr> <chr [1]>
#> 3 chr1 HAVANA exon 11869 12227 . + . <chr> <chr> <chr [1]>
#> 4 chr1 HAVANA exon 12613 12721 . + . <chr> <chr> <chr [1]>
#> 5 chr1 HAVANA exon 13221 14409 . + . <chr> <chr> <chr [1]>
#> 6 chr1 HAVANA transc… 12010 13670 . + . <chr> <chr> <chr [1]>
#> 7 chr1 HAVANA exon 12010 12057 . + . <chr> <chr> <chr [1]>
#> 8 chr1 HAVANA exon 12179 12227 . + . <chr> <chr> <chr [1]>
#> 9 chr1 HAVANA exon 12613 12697 . + . <chr> <chr> <chr [1]>
#> 10 chr1 HAVANA exon 12975 13052 . + . <chr> <chr> <chr [1]>
#> # ℹ 82 more rows
#> # ℹ 15 more variables: gene_name <list>, level <list>, hgnc_id <list>,
#> # havana_gene <list>, Parent <list>, transcript_id <list>,
#> # transcript_type <list>, transcript_name <list>,
#> # transcript_support_level <list>, tag <list>, havana_transcript <list>,
#> # exon_number <list>, exon_id <list>, ont <list>, protein_id <list>Import BLAST output.
importblast(system.file("extdata", "blastout.tsv.gz", package = "importbio"))
#> # A tibble: 36 × 12
#> query subject perc_id aln_len mismatches gap_opens q_start q_end s_start
#> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 ASSFLKSFY… ENSP00… 88.9 9 1 0 1 9 710
#> 2 ASSFLKSFY… ENSP00… 88.9 9 1 0 1 9 710
#> 3 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 4 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 5 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 6 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 7 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 8 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 9 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> 10 ASSFLKSFY… ENSP00… 100 7 0 0 1 7 58
#> # ℹ 26 more rows
#> # ℹ 3 more variables: s_end <int>, evalue <dbl>, bit_score <dbl>Import NetMHCIIpan output.
importnetmhciipan(system.file("extdata", "netmhciipan.out.gz", package = "importbio"))
#> # A tibble: 86 × 11
#> pos mhc peptide offset core core_rel id score_el perc_rank_el
#> <int> <chr> <chr> <int> <chr> <dbl> <chr> <dbl> <dbl>
#> 1 1 DRB1_0101 MAEMKTDAAT… 3 MKTD… 0.98 P9WN… 0.0980 9.99
#> 2 2 DRB1_0101 AEMKTDAATL… 2 MKTD… 0.867 P9WN… 0.0417 16.0
#> 3 3 DRB1_0101 EMKTDAATLA… 4 DAAT… 0.613 P9WN… 0.0129 28.5
#> 4 4 DRB1_0101 MKTDAATLAQ… 3 DAAT… 0.813 P9WN… 0.00916 33.4
#> 5 5 DRB1_0101 KTDAATLAQE… 2 DAAT… 0.627 P9WN… 0.00435 45.8
#> 6 6 DRB1_0101 TDAATLAQEA… 5 LAQE… 0.64 P9WN… 0.00784 35.7
#> 7 7 DRB1_0101 DAATLAQEAG… 4 LAQE… 0.773 P9WN… 0.0117 29.8
#> 8 8 DRB1_0101 AATLAQEAGN… 3 LAQE… 0.907 P9WN… 0.0161 25.6
#> 9 9 DRB1_0101 ATLAQEAGNF… 2 LAQE… 0.753 P9WN… 0.00528 42.3
#> 10 10 DRB1_0101 TLAQEAGNFE… 3 QEAG… 0.48 P9WN… 0.00186 63.6
#> # ℹ 76 more rows
#> # ℹ 2 more variables: exp_bind <dbl>, bind_level <chr>Import mhcflurry-predict output.
importmhcflurry(system.file("extdata", "mhcflurry.pred.csv.gz", package = "importbio"))
#> # A tibble: 92 × 8
#> id allele peptide mhcflurry_affinity mhcflurry_affinity_percentile
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 0 HLA-A02:01 MAEMKTDAA 19262. 11.1
#> 2 1 HLA-A02:01 AEMKTDAAT 23317. 16.5
#> 3 2 HLA-A02:01 EMKTDAATL 11060. 5.90
#> 4 3 HLA-A02:01 MKTDAATLA 24356. 18.5
#> 5 4 HLA-A02:01 KTDAATLAQ 21710. 13.9
#> 6 5 HLA-A02:01 TDAATLAQE 24373. 18.5
#> 7 6 HLA-A02:01 DAATLAQEA 17752. 9.89
#> 8 7 HLA-A02:01 AATLAQEAG 26679. 25.4
#> 9 8 HLA-A02:01 ATLAQEAGN 27336. 27.6
#> 10 9 HLA-A02:01 TLAQEAGNF 11715. 6.24
#> # ℹ 82 more rows
#> # ℹ 3 more variables: mhcflurry_processing_score <dbl>,
#> # mhcflurry_presentation_score <dbl>, mhcflurry_presentation_percentile <dbl>Import bam-readcount output.
importbamreadcount(system.file("extdata", "hg38.bwa.bamreadcount.tsv.gz", package = "importbio"))
#> # A tibble: 2,733 × 11
#> chr pos ref depth base_equal base_a base_c base_g base_t
#> <chr> <int> <chr> <int> <list> <list> <list> <list> <list>
#> 1 chr11 5224908 C 9 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 2 chr11 5224909 A 9 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 3 chr11 5224910 G 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 4 chr11 5224911 A 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 5 chr11 5224912 T 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 6 chr11 5224913 T 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 7 chr11 5224914 C 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 8 chr11 5224915 C 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 9 chr11 5224916 G 10 <tibble> <tibble> <tibble> <tibble> <tibble>
#> 10 chr11 5224917 G 11 <tibble> <tibble> <tibble> <tibble> <tibble>
#> # ℹ 2,723 more rows
#> # ℹ 2 more variables: base_n <list>, base_indel <list>#> R version 4.3.3 (2024-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.4 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
#> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
#> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] importbio_0.0.7
#>
#> loaded via a namespace (and not attached):
#> [1] crayon_1.5.2 vctrs_0.6.5 cli_3.6.2 knitr_1.45
#> [5] rlang_1.1.3 xfun_0.42 purrr_1.0.2 generics_0.1.3
#> [9] bit_4.0.5 glue_1.7.0 htmltools_0.5.7 hms_1.1.3
#> [13] fansi_1.0.6 rmarkdown_2.26 evaluate_0.23 tibble_3.2.1
#> [17] tzdb_0.4.0 fastmap_1.1.1 yaml_2.3.8 lifecycle_1.0.4
#> [21] compiler_4.3.3 dplyr_1.1.4 pkgconfig_2.0.3 tidyr_1.3.1
#> [25] rstudioapi_0.15.0 digest_0.6.35 R6_2.5.1 readr_2.1.5
#> [29] tidyselect_1.2.1 utf8_1.2.4 parallel_4.3.3 vroom_1.6.5
#> [33] pillar_1.9.0 magrittr_2.0.3 withr_3.0.0 bit64_4.0.5
#> [37] tools_4.3.3
Email me at davetang dot org (no spaces).