Addition of script to produce oncoprint #176

cbethell · 2019-10-25T14:59:09Z

Purpose/implementation

This draft PR adds the notebook which produces oncoprints given the output of strelka2, mutect2, lancet, and vardict.

The goal is to produce an oncoplot including cnv and fusion information, in addition to the snv information already displayed. For reference, here is a plot produced using a workflow authored by @jharenza:

In an attempt to adapt said workflow to our data, I discovered that the format of our data files are different from the input files used to produce the above plot. Therefore, I was unable to successfully plug our input files into the code. That being said, it seems that this may require some amount of data wrangling which is still in progress. However, please feel free to offer your relevant suggestions at any point.

Issue

This addresses issue #6 on producing an oncoprint showing the landscape of genetic lesions across PBTA.

Directions for reviewers

Is there a filtering step you feel should be added to this notebook?
Does the first plot where the data from all four callers are combined seem beneficial?
Do you feel the aesthetics of the plots are appropriate?
The features of the metadata I chose to annotate the plots further include broad_histology, short_histology, reported_gender, and tumor_descriptor. Do these features seem to be the most appropriate annotations for these plots?

The plots can be found in the plots directory of this module, and in the html output of this notebook here.

Results

Oncoprints displaying each snv callers’ output across this dataset has been produced thus far.
The output files are:

analyses/oncoprint-landscape/plots/combined_maf_oncoprint.png
analyses/oncoprint-landscape/plots/strelka2_oncoprint.png
analyses/oncoprint-landscape/plots/mutect2_oncoprint.png
analyses/oncoprint-landscape/plots/lancet_oncoprint.png
analyses/oncoprint-landscape/plots/vardict_oncoprint.png

Docker and continuous integration

The dependencies required to run the code in this pull request have been added to the project Dockerfile.
This analysis has been added to continuous integration.

Run a linter
Set the seed - Not needed.
Comments and/or documentation up to date
Double check your paths
Spell check any Rmd file or md file
Restart R and run all notebooks fresh and save

jharenza · 2019-10-25T15:20:09Z

@cbethell Thanks for working on this! This will probably be the first or second figure and most critiqued from a biological standpoint to represent the tumors landscape accurately, so I have a few thoughts:

Yes, there was some data wrangling for adding copy number and fusions to these plots. For fusions, I appended them to the MAF file, so once 04-project specific filtering and run script #166 is completed, we can use that final filtered file to add high-confidence fusions to the MAF to be integrated into the plot. This will also require you to specify Fusion as a variant classification upon reading the MAF.
For copy number, once Proposed Analysis: Copy number consensus calls #128 is completed, these can also be added. This may be tricky, as we are dealing with NGS tools instead of array, and in general, it makes more sense to add to an oncoprint focal amplifications and homozygous deletions, rather than any genes with CN changes due to broad gain/loss. For these, I had to threshold a bit, but once we see the results from the consensus calls, I think we can better tackle what this means.
Regarding the multiple MAFs, I would suggest just working with one for now (as we will use consensus SNV calls from a final MAF from Getting consensus mutations list by comparing callers #174 as input to this figure). This can be used as proof of principle.
One thing that is tricky about MAF files is that using the files as they are results in many private variants coming through into the MAF. The MUC and TTN genes, for example, are some of the largest genes in the genome and by default are most mutated, but not at hotspots. These are generally not considered cancer driver genes, so oftentimes, we will come up with a gene list for subsetting the MAF. Top N (25-50?) brain tumor driver genes, for example. For this, perhaps we create an issue to create a driver gene list, and we can potentially add this to the data release - @jaclyn-taroni - thoughts? I had created two gene driver lists for pediatric brain tumors - long and short based on the literature. We could also try using these to start and see what the plots look like?
Finally, I think that we will also want to add molecular_subtype to these plots. Currently, this is pretty sparse (and I realize MB subtypes are only denoted for RNA because that's what the classifier used to predict them, but should be added at the patient level), but will be addressed with Planned Analysis: Molecularly subtype all tumors #19.

jaclyn-taroni · 2019-10-25T15:36:42Z

Regarding the multiple MAFs, I would suggest just working with one for now (as we will use consensus SNV calls from a final MAF from #174 as input to this figure). This can be used as proof of principle.

Let's move to using a script where you accept a MAF file as a command line argument @cbethell.

For these three points:

Yes, there was some data wrangling for adding copy number and fusions to these plots. For fusions, I appended them to the MAF file, so once 04-project specific filtering and run script #166 is completed, we can use that final filtered file to add high-confidence fusions to the MAF to be integrated into the plot. This will also require you to specify Fusion as a variant classification upon reading the MAF.

For copy number, once Proposed Analysis: Copy number consensus calls #128 is completed, these can also be added. This may be tricky, as we are dealing with NGS tools instead of array, and in general, it makes more sense to add to an oncoprint focal amplifications and homozygous deletions, rather than any genes with CN changes due to broad gain/loss. For these, I had to threshold a bit, but once we see the results from the consensus calls, I think we can better tackle what this means.

Finally, I think that we will also want to add molecular_subtype to these plots. Currently, this is pretty sparse (and I realize MB subtypes are only denoted for RNA because that's what the classifier used to predict them, but should be added at the patient level), but will be addressed with Planned Analysis: Molecularly subtype all tumors #19.

We can get this code working and through review and make these updates as they come in. As far as the driver lists are concerned, let's try adding the download of the driver lists @jharenza linked to a shell script that includes the following steps:

Download driver lists.
Run the oncoplot R script.

So to accomplish step one, you could do something like (untested):

mkdir driver-lists
wget --directory-prefix=driver-lists -O brain-goi-list-long.txt https://github.com/marislab/create-pptc-pdx-oncoprints/raw/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list-old.txt 
wget --directory-prefix=driver-lists -O brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/blob/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt

- added a shell script to `wget` gene list and run `01-plot-oncoprint.R` - added optparse options to include a snv maf file, seg cnv file, and fusion file (although cnv and fusion data are not yet displayed on the oncoprint) - used snv data solely from mutect2 to produce the oncoprint (this data will be replaced by a consensus maf file once it is produced and merged) - updated `.circleci` appropriately

jaclyn-taroni

A couple things I noticed as this was coming in

jaclyn-taroni · 2019-10-25T20:02:48Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+library(maftools)
+
+# Define a color vector for plots 
+colores = c("Missense_Mutation" = "#35978f", 


Suggested change

colores = c("Missense_Mutation" = "#35978f",

colores <- c("Missense_Mutation" = "#35978f",

jaclyn-taroni · 2019-10-25T20:04:11Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+#### Specify genes -------------------------------------------------------------
+
+# Read in gene list
+goi_list <-


I would also make this a command line option.

jaclyn-taroni · 2019-10-25T20:10:02Z

analyses/oncoprint-landscape/run-oncoprint.sh

+
+mkdir driver-lists
+wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-long.txt https://github.com/marislab/create-pptc-pdx-oncoprints/raw/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list-old.txt 
+wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/blob/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt


I thought the blob -> raw was necessary and remembered to change the first one but perhaps not

Suggested change

wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/blob/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt

wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/raw/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt

jaclyn-taroni · 2019-10-25T20:21:59Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+# Get `magrittr` pipe
+`%>%` <- dplyr::`%>%`
+
+plot_oncoplot <- function(maf_file, filename){


Also think this is now a MAF object and not a MAF file.

Good point, this change will be in the next commit.

…ile` command line arguments optional - renamed `maf_file` argument in `plot_oncoplot` function to `maf_object` - removed `.gitignore` as it is no longer needed in this module - edited `wget` line to change `blob` to `raw` in genes list file path

- made a slight change to the plot dimensions - made the inclusion of a gene list optional - changed an instance of `=` to `<-`

- displayed the plot in the `README` instead of a separate markdown - added the appropriate argument to the `read.maf` function to include the cnv information if it is supplied via the command line

jaclyn-taroni

Hi @cbethell, I've reviewed and left some comments.

Below I'm splitting things up into what needs to happen as part of this pull request and what is outside of the scope of the pull request in service of keeping track of what needs to be done to satisfy #6.

Before merging

Fix the indentation issues
Have the fusion code use the standardized fusion caller format, rather than the Arriba format
Accept the oncoprint PNG filename as a command line argument
Simplify the logic for the option files (e.g., fusion, CNV)
Add a TODO statement about the copy number functionality
Make plot_oncoplot less reliant on objects in the global environment or get rid of plot_oncoplot function

In the future

Add copy number functionality
Optionally, run this for all four callers and put the PNGs in the README
Rerun this plot with the following updated data:
- Final fusion list Getting consensus mutations list by comparing callers #174
- Copy number consensus Proposed Analysis: Copy number consensus calls #128
- Add molecular subtypes Planned Analysis: Molecularly subtype all tumors #19
I don't know if such a file already exists, but I like the idea adding functionality to give the script a blacklist of genes like MUC and TTN which are likely to show up but are not of interest.

jaclyn-taroni · 2019-10-25T23:12:09Z

analyses/oncoprint-landscape/run-oncoprint.sh

+cd "$script_directory" || exit
+
+mkdir driver-lists
+wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-long.txt https://github.com/marislab/create-pptc-pdx-oncoprints/raw/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list-old.txt 


Since you've committed the files here, you can use the --no-clobber option to wget: https://stackoverflow.com/questions/4944295/skip-download-if-files-exist-in-wget

jaclyn-taroni · 2019-10-25T23:15:17Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+
+#### Plot and Save Oncoprint ---------------------------------------------------
+
+plot_oncoplot(maf_object, "maf_oncoprint.png")


The output filename should also be a command line argument. Say you wanted to run this multiple times (e.g., one for each MAF file/call). Without the ability to specify the plot filename, you would overwrite this every time.

It's unclear to me how the gene list gets used here.

Oh I see, you expect genes to be in the global environment.

Suggested change

plot_oncoplot(maf_object, "maf_oncoprint.png")

plot_oncoplot(maf_object, "maf_oncoprint.png", genes = genes)

I think setting things up this way makes it more clear.

jaclyn-taroni · 2019-10-25T23:16:37Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+#### Specify genes -------------------------------------------------------------
+
+if (!is.null(opt$goi_list)){
+# Read in gene list


Indentation here is off.

jaclyn-taroni · 2019-10-25T23:18:23Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+
+maf <- opt$maf_file
+
+if (!is.null(opt$cnv_file)) {


Any time you have if(!is.null(opt$cnv_file)) or if(!is.null(opt$fusion_file)) multiple times, it suggests that that can all be combined into a single if statement. There may be some exceptions of course, but in this case I see no reason you need to set this variable and read in the file separately before using that data.

jaclyn-taroni · 2019-10-25T23:19:18Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+#### Incorporate Fusion Data ---------------------------------------------------
+
+if (!is.null(opt$fusion_file)) {
+fus <- fusion_file


Indentation here is off in this block.

jaclyn-taroni · 2019-10-25T23:23:56Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+# Get `magrittr` pipe
+`%>%` <- dplyr::`%>%`
+
+plot_oncoplot <- function(maf_object, filename){


Suggested change

plot_oncoplot <- function(maf_object, filename){

plot_oncoplot <- function(maf_object, filename, genes = NULL){

Alternatively, if you are not planning to use this outside the context of this script, it gets used once, so it may not need to be a function. If do you plan on moving it outside this script so you can source it in multiple places, then you'd want to have the color palette as an argument.

jaclyn-taroni · 2019-10-25T23:24:46Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+  dir.create(plots_dir)
+}
+
+genes <- NULL


Remove this and use argument to plot_oncoplot instead.

You have the logic down below now: https://github.com/AlexsLemonade/OpenPBTA-analysis/pull/176/files#diff-f1245b275299730475f8b3d538c277f6R204 so I think this can come out.

jaclyn-taroni · 2019-10-25T23:30:15Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+
+# Read in cnv file
+if (!is.null(opt$cnv_file)) {
+  cnv_file <- data.table::fread(cnv, stringsAsFactors = FALSE)


When you collapse this with the logic above (line 147), add a TODO:

# TODO: <what you think the next steps will be based on what you know so far>

jaclyn-taroni · 2019-10-25T23:41:54Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+library(maftools)
+
+# Define a color vector for plots 
+colores <- c("Missense_Mutation" = "#35978f", 


You could move this to something like util/oncoplot-palette.R -- that allows you to source it from wherever and can help keep things consistent if you need to use this palette across multiple scripts. The entire contents of util/oncoplot-palette.R would be:

# <Your names> # <Link to code where it came from originally if applicable, e.g., PPTC paper repo > # <Comment about intended usage> # Define a color vector for plots color_palette <- c("Missense_Mutation" = "#35978f", "Nonsense_Mutation" = "#000000", "Frame_Shift_Del" = "#56B4E9", "Frame_Shift_Ins" = "#FFBBFF", "Splice_Site" = "#F0E442", "Translation_Start_Site" = "#191970", "Nonstop_Mutation" = "#545454", "In_Frame_Del" = "#CAE1FF", "In_Frame_Ins" = "#FFE4E1", "Stop_Codon_Ins" = "#CC79A7", "Start_Codon_Del" = "#56B4E9", "Fusion" = "#7B68EE", "Multi_Hit" = "#f46d43", "Hom_Deletion" = "#313695", "Hem_Deletion" = "#abd9e9", "Amplification" = "#c51b7d", "Loss" = "#0072B2", "Gain" = "#D55E00", "High_Level_Gain" = "#FF0000", "Multi_Hit_Fusion" = "#CD96CD")

jaclyn-taroni · 2019-10-26T00:05:27Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+if (!is.null(opt$fusion_file)) {
+fus <- fusion_file
+
+fus <- fus %>%


Because the plan is to take the final filtered set from @kgaonkar6's work over on #166, you should plan use the standardized tabular format she's using. The relevant documentation of the column I think you'll want to use is here:

OpenPBTA-analysis/analyses/fusion_filtering/01-fusion-standardization.R

Line 7 in c8a2399

# "FusionName" GeneA--GeneB ,or if fusion is intergenic then Gene1A/Gene2A--GeneB

If you want one of those files for development, you can take the command used in CI and run it from the root directory:

Rscript analyses/fusion_filtering/01-fusion-standardization.R -f "data/pbta-fusion-arriba.tsv.gz" -c "arriba" -o "scratch/arriba.tsv"

and then use scratch/arriba.tsv. There will potentially be other columns in whatever ends up being the final product out of #174, but a way to deal with that would be to only select the columns you need for this.

- added and sourced `util/oncoplot-palette.R` in `01-plot-oncoprint.R` to define color vector - accepted png output filename via command line option - removed `plot_oncoplot` custom function as it is only needed once in the script - simplified logic statements - Added `TODO` for copy number functionality - Fixed indentation issues

jaclyn-taroni

I had a few more comments @cbethell

jaclyn-taroni · 2019-10-28T18:26:51Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+  ),
+  optparse::make_option(
+    c("-c", "--cnv_file"),
+    action = "store_true",


My understanding is that you only want to use action = "store_true" if this is a logical (make_option docs)

jaclyn-taroni · 2019-10-28T18:29:51Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+  # Read in gene list
+  goi_list <-
+    read.delim(
+      file.path("driver-lists", "brain-goi-list-long.txt"),


This should be the command line option, not hardcoded.

jaclyn-taroni · 2019-10-28T18:31:36Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+    read.delim(
+      file.path("driver-lists", "brain-goi-list-long.txt"),
+      sep = "\t",
+      header = F,


Suggested change

header = F,

header = FALSE,

jaclyn-taroni · 2019-10-28T18:31:43Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+      file.path("driver-lists", "brain-goi-list-long.txt"),
+      sep = "\t",
+      header = F,
+      as.is = T


Suggested change

as.is = T

as.is = TRUE

jaclyn-taroni · 2019-10-28T18:43:44Z

analyses/oncoprint-landscape/README.md

+The structure of this folder is as follows:
+
+```
+oncoprint-landscape


This should probably be the output of tree: https://rschu.me/list-a-directory-with-tree-command-on-mac-os-x-3b2d4c4a4827

jaclyn-taroni · 2019-10-28T18:44:34Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+}
+
+genes <- NULL
+cnv_file <- NULL


Leftover from development?

jaclyn-taroni · 2019-10-28T18:45:37Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+library(maftools)
+
+# Source the color palette for plots
+source(file.path("util", "oncoplot-palette.R"))


This should utilize root_dir so it's looking in the right directory no matter where this script is called from.

jaclyn-taroni · 2019-10-28T18:49:36Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+  dir.create(plots_dir)
+}
+
+genes <- NULL


You have the logic down below now: https://github.com/AlexsLemonade/OpenPBTA-analysis/pull/176/files#diff-f1245b275299730475f8b3d538c277f6R204 so I think this can come out.

jaclyn-taroni · 2019-10-28T18:50:36Z

analyses/oncoprint-landscape/util/oncoplot-palette.R

+                   "Loss" = "#0072B2",
+                   "Gain" = "#D55E00",
+                   "High_Level_Gain" = "#FF0000",
+                   "Multi_Hit_Fusion" = "#CD96CD")


New line here

- used command line option to read in `goi_list` - Change `F` to `FALSE` and `T` to `TRUE` where applicable - removed `genes <- NULL` - changed `cnv_file <- NULL` to `cnv_file <- opt$cnv_file` - utilized `root_dir` to source `oncoplot-palette.R` - added new line to the end of `oncoplot-palette.R`

jaclyn-taroni

I left some comments about how to improve the multi-hit fusion section. Once those comments are addressed, we can get this merged. Thanks!

jaclyn-taroni · 2019-10-29T12:30:50Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+if (!is.null(opt$fusion_file)) {
+  fusion_file <- data.table::fread(opt$fusion_file, stringsAsFactors = FALSE)
+
+  #### Incorporate Fusion Data -------------------------------------------------


Can you add a #TODO here as well? Specifically I think this might need to change once we get the consensus calls (I'm not sure you'll need to do the separation in quite the same way).

jaclyn-taroni · 2019-10-29T12:34:37Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+
+# Read in fusion file
+if (!is.null(opt$fusion_file)) {
+  fusion_file <- data.table::fread(opt$fusion_file, stringsAsFactors = FALSE)


Suggested change

fusion_file <- data.table::fread(opt$fusion_file, stringsAsFactors = FALSE)

fusion_file <- data.table::fread(opt$fusion_file, data.table = FALSE, stringsAsFactors = FALSE)

probably will make things a bit easier

jaclyn-taroni · 2019-10-29T12:46:10Z

analyses/oncoprint-landscape/01-plot-oncoprint.R

+  # Separate fusion gene partners and add variant classification and center
+  fus_sep <- fusion_file %>%
+    tidyr::separate(FusionName, c("5'-gene", "3'-gene"), sep = "--")
+
+  # Determine which samples have multi-fused fusions
+  multi <- fus_sep[, c("Sample", "5'-gene", "3'-gene")]
+  multi$ID <- paste0(multi$Sample, ";", multi$`5'-gene`)
+  reformat_multi <- multi %>%
+    dplyr::group_by(ID) %>%
+    dplyr::summarise(Sample = dplyr::n()) %>%
+    as.data.frame()
+
+  reformat_multi$Variant_Classification <-
+    ifelse(reformat_multi$Sample == 1, "Fusion", "Multi_Hit_Fusion")
+  reformat_multi <- reformat_multi %>%
+    tidyr::separate(ID, c("Tumor_Sample_Barcode", "Hugo_Symbol"), sep = ";")
+  reformat_multi$Sample <- NULL
+  reformat_multi$Variant_Type <- "OTHER"


I think this section would benefit from using more R-friendly column names and it could be simplified by using additional dplyr functionality:

fus_sep <- fusion_file %>% # can add a note here about 5' and 3' tidyr::separate(FusionName, c("Gene1", "Gene2"), sep = "--") %>% dplyr::select(Sample, Gene1, Gene2) reformat_fusion <- fus_sep %>% # here we want to tally how many times the 5' gene shows up as a fusion hit # in a sample dplyr::group_by(Sample, Gene1) %>% dplyr::tally() %>% # if the sample-5' gene pair shows up more than once, call it a multi hit # fusion dplyr::mutate(Variant_Classification = dplyr::if_else(n == 1, "Fusion", "Multi_Hit_Fusion"), # required column for joining with MAF Variant_Type = "OTHER") %>% # correct format for joining with MAF dplyr::rename(Tumor_Sample_Barcode = Sample, Hugo_Symbol = Gene1) %>% dplyr::select(-n)

Should be equivalent. Then you're ready to bind reformat_fusion.

- Made fusion formatting section more R-friendly - Added `data.table = FALSE` when reading in fusion file

Addition of notebook producing oncoprints

bd34b00

jharenza self-requested a review October 25, 2019 15:07

cbethell and others added 3 commits October 25, 2019 15:47

Merge branch 'master' into oncoprint-plotting

bf965ca

Addition of md file to display produced oncoprint

d171a11

jaclyn-taroni reviewed Oct 25, 2019

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cbethell added 3 commits October 25, 2019 17:08

Included gene list as command line option

2167209

- made a slight change to the plot dimensions - made the inclusion of a gene list optional - changed an instance of `=` to `<-`

Added README.md

5abae7f

- displayed the plot in the `README` instead of a separate markdown - added the appropriate argument to the `read.maf` function to include the cnv information if it is supplied via the command line

cbethell changed the title ~~In Progress: Addition of notebook to produce oncoprints~~ Addition of script to produce oncoprint Oct 28, 2019

cbethell marked this pull request as ready for review October 28, 2019 11:39

jaclyn-taroni reviewed Oct 28, 2019

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cbethell and others added 3 commits October 28, 2019 12:40

Merge branch 'master' into oncoprint-plotting

da19128

Indentation fix

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jaclyn-taroni reviewed Oct 28, 2019

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jaclyn-taroni approved these changes Oct 29, 2019

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cbethell and others added 2 commits October 29, 2019 09:41

Added TODO comment to fusion section

f61a628

- Made fusion formatting section more R-friendly - Added `data.table = FALSE` when reading in fusion file

Move above SNV caller analysis in CI

b733812

jaclyn-taroni merged commit 4254f93 into AlexsLemonade:master Oct 29, 2019

cbethell mentioned this pull request Oct 29, 2019

Addition of cnv data to oncoprint #182

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cbethell mentioned this pull request Nov 7, 2019

Update oncoprint with focal CN data #243

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cbethell deleted the oncoprint-plotting branch December 18, 2019 19:13

	colores = c("Missense_Mutation" = "#35978f",
	colores <- c("Missense_Mutation" = "#35978f",

	wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/blob/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt
	wget --directory-prefix=driver-lists -O driver-lists/brain-goi-list-short.txt https://github.com/marislab/create-pptc-pdx-oncoprints/raw/2c9ed2a2331bcef3003d6aa25a130485d76a3535/data/brain-goi-list.txt


		#### Plot and Save Oncoprint ---------------------------------------------------

		plot_oncoplot(maf_object, "maf_oncoprint.png")

	plot_oncoplot <- function(maf_object, filename){
	plot_oncoplot <- function(maf_object, filename, genes = NULL){

	fusion_file <- data.table::fread(opt$fusion_file, stringsAsFactors = FALSE)
	fusion_file <- data.table::fread(opt$fusion_file, data.table = FALSE, stringsAsFactors = FALSE)

Addition of script to produce oncoprint #176

Addition of script to produce oncoprint #176

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cbethell commented Oct 25, 2019 • edited Loading

Purpose/implementation

Issue

Directions for reviewers

Results

Docker and continuous integration

jharenza commented Oct 25, 2019 • edited Loading

jaclyn-taroni commented Oct 25, 2019 • edited Loading

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Before merging

In the future

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cbethell commented Oct 25, 2019 •

edited

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jharenza commented Oct 25, 2019 •

edited

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jaclyn-taroni commented Oct 25, 2019 •

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