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+Integrate molecular subtyping results
+Krutika Gaonkar for D3b
+2020
+ +The purpose of this notebook is to integrate molecular subtyping results from molecular-subtyping-pathology with pbta-histologies-base.tsv.
Here we will use pbta-histologies-base.tsv in which integrated_diagnosis,Notes and molecular_subtype are all NA. Through all the following molecular subtyping modules:
-
+
- molecular-subtyping-MB +
- molecular-subtyping-CRANIO +
- molecular-subtyping-EPN +
- molecular-subtyping-embryonal +
- molecular-subtyping-EWS +
- molecular-subtyping-neurocytoma +
- molecular-subtyping-HGG +
- molecular-subtyping-LGAT +
- molecular-subtyping-pathology +
We gathered and updated molecular-subtype AND integrated_diagnosis AND broad_histology AND short_histology for these histologies.
+In this notebook we will add the molecular subtyping information compiled and updated by pathology review in molecular-subtyping-pathology/compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv to create the pbta-histologies.tsv for the same release. If samples are not processed by a molecular-subtyping-* module then the br
In adddition, for samples that where pathology_diagnosis is “Other” we also update the file broad_histology and short_histology from a manual review of WHO terms.
+
+
+
+Set up
+ + + +library(tidyverse)
+data_dir <- "../../data/"
+
+
+base_histology <- read_tsv(file.path(data_dir,"pbta-histologies-base.tsv"),
+ col_types = readr::cols(molecular_subtype = readr::col_character(),
+ short_histology = readr::col_character(),
+ broad_histology = readr::col_character(),
+ Notes = readr::col_character())) %>%
+ unique()
+
+Read molecular-subtyping-pathology results
+Reading molecular_subtype, integrated_diagnosis, short_histology, broad_histology and Notes from compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv
+compiled_subtyping<-read_tsv(file.path("..", "molecular-subtyping-pathology", "results", "compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv"))
+Update “Other” sample broad/short histology and harmonized_diagnosis and add to compiled_subtyping
+Other_subtypes <- read_tsv(file.path("input","pathology_dx and pathology_free_text_diagnosis to broad_histology for subtyping module - rules_without_subtype_WIP.tsv"))
+
+compiled_subtyping_other <- base_histology %>%
+ select(
+ Kids_First_Participant_ID ,
+ sample_id,
+ Kids_First_Biospecimen_ID,
+ molecular_subtype,
+ integrated_diagnosis,
+ pathology_diagnosis,
+ pathology_free_text_diagnosis,
+ tumor_descriptor
+) %>%
+ # remove Kids_First_Biospecimen_ID which are subtypes "ETMR/Embryonal"
+ filter(!Kids_First_Biospecimen_ID %in% compiled_subtyping$Kids_First_Biospecimen_ID) %>%
+ # get pathology_diagnosis=="Other"
+ filter(pathology_diagnosis=="Other") %>%
+ left_join(Other_subtypes,by=c("pathology_free_text_diagnosis")) %>%
+ mutate(Notes = "Updated by manual review of WHO diagnosis") %>%
+select(
+ # gather only columns needed to format as `compiled_subtyping`
+ Kids_First_Participant_ID ,
+ sample_id,
+ Kids_First_Biospecimen_ID,
+ molecular_subtype,
+ integrated_diagnosis,
+ tumor_descriptor,
+ broad_histology,
+ short_histology,
+ Notes,
+ # adding harmonized_diagnosis from manual review
+ # for pathology_diagnosis=="Other"
+ harmonized_diagnosis
+) %>%
+ unique()
+
+
+# combined OpenPBTA subtypes and manual "Other" subtypes
+compiled_subtyping <- compiled_subtyping_other %>%
+ bind_rows(compiled_subtyping)
+
+
+Add molecular-subtyping-pathology results
+We will add molecular_subtype, integrated_diagnosis and Notes from compiled_subtyping
short_histology and broad_histology will be added from base histology for samples that are not subtyped as part of molecular-subtype-pathology
+histology <- base_histology %>%
+ select(-Notes,-molecular_subtype,-integrated_diagnosis) %>%
+ left_join(compiled_subtyping,by=c("Kids_First_Biospecimen_ID","sample_id","Kids_First_Participant_ID","tumor_descriptor"),suffix=c(".base",".subtyped")) %>%
+ unique() %>%
+ mutate(
+ broad_histology = if_else(!is.na(broad_histology.subtyped),
+ broad_histology.subtyped,
+ broad_histology.base),
+ short_histology = if_else(!is.na(short_histology.subtyped),
+ short_histology.subtyped,
+ short_histology.base),
+ harmonized_diagnosis =
+ case_when(!is.na(integrated_diagnosis) ~ integrated_diagnosis,
+ is.na(integrated_diagnosis) &
+ !is.na(harmonized_diagnosis) ~ harmonized_diagnosis,
+ is.na(integrated_diagnosis) &
+ is.na(harmonized_diagnosis) &
+ !is.na(pathology_diagnosis) ~ pathology_diagnosis
+ ))
+
+Check if any duplicates
+ + + +dup_ids<-histology$Kids_First_Biospecimen_ID[duplicated(histology$Kids_First_Biospecimen_ID)]
+
+histology[which(histology$Kids_First_Biospecimen_ID %in% dup_ids),]No duplicates
+
+
+Check if broad_histology, short_histology or harmonized_diagnosis
+Are there NA in broad_histology, short_histology or harmonized_diagnosis
+ + + +histology %>%
+ filter(sample_type=="Tumor",
+ (is.na(broad_histology)| is.na(short_histology)| is.na(harmonized_diagnosis))) %>%
+ tally()
+No NAs in broad_histology, short_histology or harmonized_diagnosis
+Just a note, integrated_diagnosis is expected to be NA for samples where subtyping is not performed or if molecular_subtype is “XYZ,To be classified”. This means no evidence was provided/available for these samples so we are not able to add integrated_diagnosis.
+
+Check differences in broad_histology
+Checking for differences in broad_histology to look for changes in molecular_subtype
+ + + +diff_broad_histology<- histology %>%
+ filter(toupper(broad_histology.base) != toupper(broad_histology.subtyped)) %>%
+ select(Kids_First_Biospecimen_ID,starts_with("broad_histology"),starts_with("short_histology")) %>%
+ unique()
+
+diff_broad_histology
+
+Check differences in short_histology
+Here we want to check for short_histology changes not part of Check differences in broad_histology chunk. This will help us check what string assignment path_dx to short_histology mapping has changed from molecular-subtyping-pathology
+histology %>%
+ filter(!Kids_First_Biospecimen_ID %in% diff_broad_histology$Kids_First_Biospecimen_ID) %>%
+ filter(toupper(short_histology.base) != toupper(short_histology.subtyped)
+ ) %>%
+ select(Kids_First_Biospecimen_ID,starts_with("broad_histology"),starts_with("short_histology")) %>%
+ unique()
+The above 172 changes occurred because of changes in string value assignment In compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv a sample with broad_histology that is Ependymal tumor is EPN, but in pbta-histologies-base.tsv it is Ependymoma. For samples where broad_histology is Embryonal tumor, short_histology is also Embryonal tumor but in base histology it was ETMR.
45 Benign ,Non-(CNS) tumor and other samples where pathology_diagnosis == “Other”,have short_histology updated from manual review of WHO diagnosis terms.
+
+
+Save
+Let’s save the final file.
+But first need to remove broad_histology.base, broad_histology.subtyped and short_histology.base and short_histology.subtyped
+ + + +histology %>%
+ select(-broad_histology.base,
+ -broad_histology.subtyped,
+ - short_histology.base,
+ -short_histology.subtyped) %>%
+ write_tsv("results/pbta-histologies.tsv")---
title: "Integrate molecular subtyping results"
output: 
  html_notebook:
    toc: true
    toc_float: true
author: Krutika Gaonkar for D3b
date: 2020
---

The purpose of this notebook is to integrate molecular subtyping results from 
[molecular-subtyping-pathology](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-pathology) with `pbta-histologies-base.tsv`.

Here we will use `pbta-histologies-base.tsv` in which integrated_diagnosis,Notes and molecular_subtype are all NA. Through all the following molecular subtyping modules:

- molecular-subtyping-MB
- molecular-subtyping-CRANIO
- molecular-subtyping-EPN
- molecular-subtyping-embryonal
- molecular-subtyping-EWS
- molecular-subtyping-neurocytoma
- molecular-subtyping-HGG
- molecular-subtyping-LGAT
- molecular-subtyping-pathology


We gathered and updated molecular-subtype AND integrated_diagnosis AND broad_histology AND short_histology for these histologies.

In this notebook we will add the molecular subtyping information compiled and updated by pathology review in `molecular-subtyping-pathology/compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv` to create the `pbta-histologies.tsv` for the same release. If samples are not processed by a molecular-subtyping-* module then the br

In adddition, for samples that where pathology_diagnosis is "Other" we also update the file broad_histology and short_histology from a manual review of WHO terms.

![](https://user-images.githubusercontent.com/34580719/103105428-c63e1f80-45fb-11eb-8548-28bcba0b2dba.png)

## Set up

```{r}
library(tidyverse)
data_dir <- "../../data/"


base_histology <- read_tsv(file.path(data_dir,"pbta-histologies-base.tsv"),
                           col_types = readr::cols(molecular_subtype = readr::col_character(),
                                                   short_histology = readr::col_character(),
                           broad_histology = readr::col_character(),
                           Notes = readr::col_character())) %>%
  unique()
```

### Read molecular-subtyping-pathology results

Reading molecular_subtype, integrated_diagnosis, short_histology, broad_histology and Notes from `compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv` 

```{r}

compiled_subtyping<-read_tsv(file.path("..", "molecular-subtyping-pathology", "results", "compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv"))

```

Update "Other" sample broad/short histology and harmonized_diagnosis and add to `compiled_subtyping`

```{r}

Other_subtypes <- read_tsv(file.path("input","pathology_dx and pathology_free_text_diagnosis to broad_histology for subtyping module - rules_without_subtype_WIP.tsv"))

compiled_subtyping_other <- base_histology %>%
  select(
  Kids_First_Participant_ID ,
  sample_id,
  Kids_First_Biospecimen_ID,
  molecular_subtype,
  integrated_diagnosis,
  pathology_diagnosis,
  pathology_free_text_diagnosis,
  tumor_descriptor
) %>%
  # remove Kids_First_Biospecimen_ID which are subtypes "ETMR/Embryonal"
  filter(!Kids_First_Biospecimen_ID %in% compiled_subtyping$Kids_First_Biospecimen_ID) %>%
  # get pathology_diagnosis=="Other"
  filter(pathology_diagnosis=="Other") %>%
  left_join(Other_subtypes,by=c("pathology_free_text_diagnosis")) %>%
  mutate(Notes = "Updated by manual review of WHO diagnosis") %>%
select(
  # gather only columns needed to format as `compiled_subtyping`
  Kids_First_Participant_ID ,
  sample_id,
  Kids_First_Biospecimen_ID,
  molecular_subtype,
  integrated_diagnosis,
  tumor_descriptor,
  broad_histology,
  short_histology,
  Notes,
  # adding harmonized_diagnosis from manual review 
  # for pathology_diagnosis=="Other"
  harmonized_diagnosis
) %>%
  unique()


# combined OpenPBTA subtypes and manual "Other" subtypes
compiled_subtyping <- compiled_subtyping_other %>%
  bind_rows(compiled_subtyping)

```



### Add molecular-subtyping-pathology results

We will add molecular_subtype, integrated_diagnosis and Notes from `compiled_subtyping`

short_histology and broad_histology will be added from base histology for samples that are not subtyped as part of `molecular-subtype-pathology`

```{r}

histology <- base_histology %>% 
  select(-Notes,-molecular_subtype,-integrated_diagnosis) %>%
  left_join(compiled_subtyping,by=c("Kids_First_Biospecimen_ID","sample_id","Kids_First_Participant_ID","tumor_descriptor"),suffix=c(".base",".subtyped")) %>%
  unique() %>%
  mutate(
    broad_histology = if_else(!is.na(broad_histology.subtyped),
                              broad_histology.subtyped,
                              broad_histology.base),
    short_histology = if_else(!is.na(short_histology.subtyped),
                              short_histology.subtyped,
                              short_histology.base),
    harmonized_diagnosis = 
      case_when(!is.na(integrated_diagnosis) ~ integrated_diagnosis,
                is.na(integrated_diagnosis) & 
                  !is.na(harmonized_diagnosis) ~ harmonized_diagnosis,
                is.na(integrated_diagnosis) & 
                  is.na(harmonized_diagnosis) &
                  !is.na(pathology_diagnosis) ~ pathology_diagnosis
    )) 
```



### Check if any duplicates

```{r}
dup_ids<-histology$Kids_First_Biospecimen_ID[duplicated(histology$Kids_First_Biospecimen_ID)]

histology[which(histology$Kids_First_Biospecimen_ID %in% dup_ids),]
```

No duplicates

### Check if broad_histology, short_histology or harmonized_diagnosis

Are there NA in broad_histology, short_histology or harmonized_diagnosis

```{r}
histology %>% 
  filter(sample_type=="Tumor",
         (is.na(broad_histology)| is.na(short_histology)| is.na(harmonized_diagnosis))) %>%
  tally()

```

No NAs in broad_histology, short_histology or harmonized_diagnosis

Just a note, integrated_diagnosis is expected to be `NA` for samples where subtyping is not performed or if molecular_subtype is "XYZ,To be classified". 
This means no evidence was provided/available for these samples so we are not able to add integrated_diagnosis.

#### Check differences in broad_histology 
Checking for differences in broad_histology to look for changes in molecular_subtype 


```{r}
diff_broad_histology<- histology %>%
  filter(toupper(broad_histology.base) != toupper(broad_histology.subtyped)) %>%
  select(Kids_First_Biospecimen_ID,starts_with("broad_histology"),starts_with("short_histology")) %>%
  unique()

diff_broad_histology
```

#### Check differences in short_histology
Here we want to check for short_histology changes not part of `Check differences in broad_histology` chunk.
This will help us check what string assignment path_dx to short_histology mapping has changed from `molecular-subtyping-pathology`

```{r}

histology %>% 
  filter(!Kids_First_Biospecimen_ID %in% diff_broad_histology$Kids_First_Biospecimen_ID) %>%
   filter(toupper(short_histology.base) != toupper(short_histology.subtyped) 
         ) %>%
  select(Kids_First_Biospecimen_ID,starts_with("broad_histology"),starts_with("short_histology")) %>%
  unique() 

```
The above 172 changes occurred because of changes in string value assignment
In `compiled_molecular_subtypes_with_clinical_pathology_feedback.tsv` a sample with broad_histology that is `Ependymal tumor` is `EPN`, but in `pbta-histologies-base.tsv` it is `Ependymoma`.
For samples where broad_histology is `Embryonal tumor`, short_histology is also `Embryonal tumor` but in base histology it was `ETMR`.

45 Benign ,Non-(CNS) tumor and other samples where pathology_diagnosis == "Other",have short_histology updated from manual review of WHO diagnosis terms.

### Save
Let's save the final file.

But first need to remove broad_histology.base, broad_histology.subtyped and short_histology.base
 and short_histology.subtyped

```{r}
histology %>% 
  select(-broad_histology.base,
         -broad_histology.subtyped,
         - short_histology.base,
         -short_histology.subtyped) %>%
  write_tsv("results/pbta-histologies.tsv")
```

+
+
+