In bailey-lab/miplicorn: A Framework for Molecular Inversion Probe and Amplicon Analysis

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(miplicorn)

data <- tibble::tribble(
  ~sample, ~gene_id, ~gene, ~mutation_name, ~exonic_func, ~aa_change, ~targeted, ~coverage,
  "LA-05-37", "PF3D7_0709000", "crt", "crt-Cys72Ser", "missense_variant", "Cys72Ser", "Yes", 1716,
  "KO-05-62", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu187Lys", "missense_variant", "Glu187Lys", "No", 246,
  "HO-05-13", "PF3D7_1451200", "PF3D7-1451200", "PF3D7-1451200-Asn71Asn", "synonymous_variant", "Asn71Asn", "Yes", 1,
  "TO-05-43", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu121Lys", "missense_variant", "Glu121Lys", "No", 40,
  "KO-05-45", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu405Lys", "missense_variant", "Glu405Lys", "No", 0,
  "KS-05-95", "PF3D7_0709000", "crt", "crt-Ala220Ser", "missense_variant", "Ala220Ser", "Yes", 1,
  "AR-05-25", "PF3D7_0810800", "dhps", "dhps-Ile431Val", "missense_variant", "Ile431Val", "Yes", 274,
  "HO-05-52", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Ser283Leu", "missense_variant", "Ser283Leu", "No", 736,
  "KN-05-54", "PF3D7_1012700", "pph", "pph-Asn1189_Asn1194del", "disruptive_inframe_deletion", "Asn1189_Asn1194del", "No", 0,
  "LA-05-100", "PF3D7_0417200", "dhfr-ts", "dhfr-ts-Cys59Arg", "missense_variant", "Cys59Arg", "Yes", 17
)

How can I add metadata to my data?

To add metadata to your metadata, you must read the metadata file as an R object and then combine the result with your data.

Metadata is often saved as a delimited file—most commonly a CSV (comma separated values) or a TSV (tab separated values)—or an excel file. There are several packages that can be used to read in such files, but we recommend the use of {vroom} for delimited files and {readxl} for excel files.

metadata <- vroom::vroom("path/to/file")
# OR
metadata <- readxl::read_excel("path/to/file")

metadata <- tibble::tribble(
  ~ID, ~District, ~Facility,
  "LA-05-37", "Lamwo", "Padibe",
  "KO-05-62", "Kole", "Aboke",
  "HO-05-13", "Hoima", "Kigorobya",
  "TO-05-43", "Tororo", "Nagongera",
  "KO-05-45", "Kole", "Aboke",
  "KS-05-95", "Kasese", "Karambi",
  "AR-05-25", "Arua", "Opia",
  "HO-05-52", "Hoima", "Kigorobya",
  "KN-05-54", "Kanungu", "Kihihi",
  "LA-05-100", "Lamwo", "Padibe"
)

After reading in your metadata, you can add the metadata to your data frame using one of {dplyr}'s mutating joins.

dplyr::left_join(data, metadata, by = c("sample" = "ID"))

Note that you may need to change the by argument to reflect the proper column name of the metadata.

My sample names do not match

In the case where your sample names do not match, first make sure that you are reading in the correct files! In some cases, your data and metadata sample names may be slightly different. For example, consider a dataset with the following sample names:

data_misformatted <- tibble::tribble(
  ~sample, ~gene_id, ~gene, ~mutation_name, ~exonic_func, ~aa_change, ~targeted, ~coverage,
  "LA-05-37-ug-sur-2020-1", "PF3D7_0709000", "crt", "crt-Cys72Ser", "missense_variant", "Cys72Ser", "Yes", 1716,
  "KO-05-62-ug-sur-2020-1", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu187Lys", "missense_variant", "Glu187Lys", "No", 246,
  "HO-05-13-ug-sur-2020-1", "PF3D7_1451200", "PF3D7-1451200", "PF3D7-1451200-Asn71Asn", "synonymous_variant", "Asn71Asn", "Yes", 1,
  "TO-05-43-ug-sur-2020-1", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu121Lys", "missense_variant", "Glu121Lys", "No", 40,
  "KO-05-45-ug-sur-2020-1", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Glu405Lys", "missense_variant", "Glu405Lys", "No", 0,
  "KS-05-95-ug-sur-2020-1", "PF3D7_0709000", "crt", "crt-Ala220Ser", "missense_variant", "Ala220Ser", "Yes", 1,
  "AR-05-25-ug-sur-2020-1", "PF3D7_0810800", "dhps", "dhps-Ile431Val", "missense_variant", "Ile431Val", "Yes", 274,
  "HO-05-52-ug-sur-2020-1", "PF3D7_1133400", "PF3D7_1133400", "PF3D7_1133400-Ser283Leu", "missense_variant", "Ser283Leu", "No", 736,
  "KN-05-54-ug-sur-2020-1", "PF3D7_1012700", "pph", "pph-Asn1189_Asn1194del", "disruptive_inframe_deletion", "Asn1189_Asn1194del", "No", 0,
  "LA-05-100-ug-sur-2020-1", "PF3D7_0417200", "dhfr-ts", "dhfr-ts-Cys59Arg", "missense_variant", "Cys59Arg", "Yes", 17
)
data_misformatted$sample

In order to add your metadata to this dataset, you must first perform some string manipulation so that the sample names in the dataset and metadata align. To do so, you can leverage the {stringr} package.

data_formatted <- data_misformatted %>%
  dplyr::mutate(sample = stringr::str_remove(sample, "-ug.*"))

You can then use {dplyr} as before:

dplyr::left_join(data_formatted, metadata, by = c("sample" = "ID"))

How can I combine multiple probe sets?

In order to combine multiple probe sets, it is first important to ensure that you plan to conduct the same analysis for each probe set. If you are not, you may want to reconsider combining multiple probe sets. Assuming you want to combine the same type of data for each probe set, you can simply bind the rows using {dplyr}.

probe_1 <- tibble::tribble(
  ~sample, ~chrom, ~pos, ~ref, ~alt, ~mutation_name, ~targeted, ~coverage,
  "AR-05-54", "chr13", "1629329", "AATAAATATATATAT", "A", "chr13:1629329:AATAAATATATATAT:A", "No", 0,
  "AR-05-73", "chr13", "1719135", "A", "T", "chr13:1719135:A:T", "No", 23,
  "KS-05-35", "chr8", "495991", "C", "T", "chr8:495991:C:T", "No", 0,
  "KN-05-43", "chr13", "1701344", "TAT", "A", "chr13:1701344:TAT:A", "No", 10,
  "MU-05-69", "chr13", "1713479", "C", "T", "chr13:1713479:C:T", "No", 3,
  "JI-05-82", "chr13", "1706967", "C", "A", "chr13:1706967:C:A", "No", 0,
  "JI-05-28", "chr13", "1706000", "A", "G", "chr13:1706000:A:G", "No", 10,
  "AG-05-28", "chr13", "1706978", "GATTAGATAAAAG", "TATTATAAAAAAAA", "chr13:1706978:GATTAGATAAAAG:TATTATAAAAAAAA", "No", 0,
  "AG-05-82", "chr4", "848676", "T", "A", "chr4:848676:T:A", "No", 0,
  "KS-05-63", "chr4", "736960", "C", "T", "chr4:736960:C:T", "No", 0
)

probe_2 <- tibble::tribble(
  ~sample, ~chrom, ~pos, ~ref, ~alt, ~mutation_name, ~targeted, ~coverage,
  "AR-05-54", "chr13", "958382", "T", "C", "chr13:958382:T:C", "No", 241,
  "AR-05-73", "chr13", "1726643", "A", "G", "chr13:1726643:A:G", "No", 185,
  "KS-05-35", "chr13", "1649722", "T", "C", "chr13:1649722:T:C", "No", 14,
  "KN-05-43", "chr13", "958465", "A", "G", "chr13:958465:A:G", "No", 517,
  "MU-05-69", "chr13", "958389", "C", "T", "chr13:958389:C:T", "No", 0,
  "JI-05-82", "chr13", "748341", "CATATAT", "C", "chr13:748341:CATATAT:C", "No", 0,
  "JI-05-28", "chr13", "1649445", "C", "A", "chr13:1649445:C:A", "No", 78,
  "AG-05-28", "chr8", "550212", "G", "A", "chr8:550212:G:A", "No", 150,
  "AG-05-82", "chr13", "1649307", "T", "A", "chr13:1649307:T:A", "No", 3,
  "KS-05-63", "chr13", "958443", "T", "C", "chr13:958443:T:C", "No", 2
)

probe_3 <- tibble::tribble(
  ~sample, ~chrom, ~pos, ~ref, ~alt, ~mutation_name, ~targeted, ~coverage,
  "AR-05-54", "chr4", "1121437", "G", "A", "chr4:1121437:G:A", "No", 3,
  "AR-05-73", "chr8", "714194", "T", "TATATATATATATATATAG", "chr8:714194:T:TATATATATATATATATAG", "No", 0,
  "KS-05-35", "chr13", "1868715", "A", "C", "chr13:1868715:A:C", "No", 3,
  "KN-05-43", "chr4", "516691", "A", "G", "chr4:516691:A:G", "No", 60,
  "MU-05-69", "chr13", "2512415", "C", "T", "chr13:2512415:C:T", "No", 87,
  "JI-05-82", "chr4", "835402", "T", "C", "chr4:835402:T:C", "No", 1,
  "JI-05-28", "chr8", "554378", "TA", "T", "chr8:554378:TA:T", "No", 43,
  "AG-05-28", "chr8", "501607", "AAAAATATATATAT", "A", "chr8:501607:AAAAATATATATAT:A", "No", 0,
  "AG-05-82", "chr4", "1089817", "T", "C", "chr4:1089817:T:C", "No", 83,
  "KS-05-63", "chr4", "390103", "TTAATAATAATAATAATAA", "T", "chr4:390103:TTAATAATAATAATAATAA:T", "No", 67
)

dplyr::bind_rows(
  list(probe_1 = probe_1, probe_2 = probe_2, probe_3 = probe_3),
  .id = "probe_set"
)

bailey-lab/miplicorn documentation built on March 19, 2023, 7:40 p.m.