From this comment on #182:

may advise starting with ATRT’s and SMARCB1 deletions

Here, I’m looking at the output of 01-prepare-cn-file.R to see if we recover that information in the segment to gene mapping. The CNVkit SEG file was used for results/annotated_cn.tsv.

`%>%` <- dplyr::`%>%`
Registered S3 method overwritten by 'dplyr':
  method           from
  print.rowwise_df

Read in data

# read in the output of `01-prepare-cn-file.R`
annotation_cn <- readr::read_tsv(file.path("results", "annotated_cn.tsv"))
Parsed with column specification:
cols(
  gene_symbol = col_character(),
  biospecimen_id = col_character(),
  label = col_character(),
  copy_number = col_double()
)
# read in the clinical file that has the disease type information
histologies_df <- readr::read_tsv(file.path("..", "..", "data", 
                                            "pbta-histologies.tsv"))
Parsed with column specification:
cols(
  .default = col_character(),
  OS_days = col_double(),
  age_last_update_days = col_double(),
  normal_fraction = col_double(),
  tumor_fraction = col_double(),
  tumor_ploidy = col_double()
)
See spec(...) for full column specifications.

Look at copy number information for ATRT

# get ATRT biospecimen identifiers
atrt_specimens <- histologies_df %>%
  dplyr::filter(disease_type_new == "Atypical Teratoid Rhabdoid Tumor") %>%
  dplyr::pull(Kids_First_Biospecimen_ID)
LS0tCnRpdGxlOiAiU2VnbWVudCB0byBnZW5lIG1hcHBpbmcgaW4gQVRSVCIKb3V0cHV0OiBodG1sX25vdGVib29rCmF1dGhvcjogSi4gVGFyb25pIGZvciBBTFNGIENDREwKZGF0ZTogMjAxOQotLS0KCkZyb20gW3RoaXMgY29tbWVudF0oaHR0cHM6Ly9naXRodWIuY29tL0FsZXhzTGVtb25hZGUvT3BlblBCVEEtYW5hbHlzaXMvcHVsbC8xODIjZGlzY3Vzc2lvbl9yMzQwNTg3OTY4KSBvbiAjMTgyOgoKPiBtYXkgYWR2aXNlIHN0YXJ0aW5nIHdpdGggQVRSVCdzIGFuZCBTTUFSQ0IxIGRlbGV0aW9ucwoKSGVyZSwgSSdtIGxvb2tpbmcgYXQgdGhlIG91dHB1dCBvZiBgMDEtcHJlcGFyZS1jbi1maWxlLlJgIHRvIHNlZSBpZiB3ZSByZWNvdmVyIHRoYXQgaW5mb3JtYXRpb24gaW4gdGhlIHNlZ21lbnQgdG8gZ2VuZSBtYXBwaW5nLgpUaGUgQ05Wa2l0IFNFRyBmaWxlIHdhcyB1c2VkIGZvciBgcmVzdWx0cy9hbm5vdGF0ZWRfY24udHN2YC4KCmBgYHtyfQpgJT4lYCA8LSBkcGx5cjo6YCU+JWAKYGBgCgojIyMgUmVhZCBpbiBkYXRhCgpgYGB7cn0KIyByZWFkIGluIHRoZSBvdXRwdXQgb2YgYDAxLXByZXBhcmUtY24tZmlsZS5SYAphbm5vdGF0aW9uX2NuIDwtIHJlYWRyOjpyZWFkX3RzdihmaWxlLnBhdGgoInJlc3VsdHMiLCAiYW5ub3RhdGVkX2NuLnRzdiIpKQojIHJlYWQgaW4gdGhlIGNsaW5pY2FsIGZpbGUgdGhhdCBoYXMgdGhlIGRpc2Vhc2UgdHlwZSBpbmZvcm1hdGlvbgpoaXN0b2xvZ2llc19kZiA8LSByZWFkcjo6cmVhZF90c3YoZmlsZS5wYXRoKCIuLiIsICIuLiIsICJkYXRhIiwgCiAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgICAgInBidGEtaGlzdG9sb2dpZXMudHN2IikpCmBgYAoKIyMjIExvb2sgYXQgY29weSBudW1iZXIgaW5mb3JtYXRpb24gZm9yIEFUUlQKCmBgYHtyfQojIGdldCBBVFJUIGJpb3NwZWNpbWVuIGlkZW50aWZpZXJzCmF0cnRfc3BlY2ltZW5zIDwtIGhpc3RvbG9naWVzX2RmICU+JQogIGRwbHlyOjpmaWx0ZXIoZGlzZWFzZV90eXBlX25ldyA9PSAiQXR5cGljYWwgVGVyYXRvaWQgUmhhYmRvaWQgVHVtb3IiKSAlPiUKICBkcGx5cjo6cHVsbChLaWRzX0ZpcnN0X0Jpb3NwZWNpbWVuX0lEKQpgYGAKCmBgYHtyfQojIGZpbHRlciB0aGUgZ2VuZS1sZXZlbCBDTiBpbmZvcm1hdGlvbiB0byBBVFJUIHNhbXBsZXMgYW5kIGdlbmUgc3ltYm9scwojIGNvbnRhaW5pbmcgJ1NNQVJDJwphbm5vdGF0aW9uX2NuICU+JQogIGRwbHlyOjpmaWx0ZXIoYmlvc3BlY2ltZW5faWQgJWluJSBhdHJ0X3NwZWNpbWVucywKICAgICAgICAgICAgICAgIGdyZXBsKCJTTUFSQ0IxIiwgZ2VuZV9zeW1ib2wpKQpgYGAKCg==