PBTA Histologies v19 Part 8 of N: Run molecular subtyping (#1028)

* v19 release

* adding updated subtypes for v19

* add embryonal subtype

* adding v19 from adapt release; temp fix 7316-1889

* update s3 bucket

* re-run with fixed hist

* emb rerun

* add tp53-nf1-scoring to subtyping

* updated hist cols rerun

* arrange by Sample

* Delete 05-QC_putative_onco_fusion_dustribution.nb.html

* Update scripts/run-for-subtyping.sh

Co-authored-by: jashapiro <josh.shapiro@ccdatalab.org>

* update VEP anno rerun

* add path_free_text subtypes to mol subtype integrate

* rerun bindrows

* rerun harm_dx meningioma

* rerun to add tumor_descriptor

* Update analyses/molecular-subtyping-pathology/pathology_free_text-subtyping-meningioma.Rmd

Co-authored-by: Jo Lynne Rokita <jharenza@gmail.com>

* Update download-data.sh

* adding order to output

* Update run-subtyping-aggregation.sh

* Update run-subtyping-aggregation.sh

* Update pathology_free_text-subtyping-meningioma.Rmd

* rerun

* raange Sample,FusionName

Co-authored-by: Ubuntu <ubuntu@ip-10-21-3-210.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-10-21-3-30.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-10-21-3-38.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-10-21-3-32.ec2.internal>
Co-authored-by: Joshua Shapiro <josh.shapiro@ccdatalab.org>
Co-authored-by: Jo Lynne Rokita <jharenza@gmail.com>

analyses/molecular-subtyping-CRANIO/00-craniopharyngiomas-molecular-subtype.nb.html

@@ -3026,7 +3026,7 @@ <h2>Directories and File Inputs/Outputs</h2>
 snv_df &lt;-
   read_tsv(file.path(root_dir, &quot;data&quot;, &quot;pbta-snv-consensus-mutation.maf.tsv.gz&quot;))</code></pre>
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 <pre><code>Parsed with column specification:
 cols(
   .default = col_character(),
@@ -3041,6 +3041,7 @@ <h2>Directories and File Inputs/Outputs</h2>
   n_alt_count = col_double(),
   ALLELE_NUM = col_double(),
   vcf_pos = col_double(),
+  HotSpotAllele = col_double(),
   VAF = col_double()
 )
 See spec(...) for full column specifications.</code></pre>

analyses/molecular-subtyping-CRANIO/results/CRANIO_defining_lesions.tsv

@@ -19,7 +19,6 @@ PT_BZKJR4GK	7316-561	BS_NTXHP7QR	BS_EMMF4PZX	6565	FALSE	FALSE
 PT_CEWNZVKF	7316-124	BS_MWXDJFWW	BS_PRR8K9GE	3725	TRUE	FALSE
 PT_E3Y5BBSF	7316-3071	BS_W8DA9AXT	BS_RFMQ7T0T	1555	TRUE	FALSE
 PT_EC8R84NM	7316-341	BS_CXDKK6KS	BS_7T1J3KET	1344	TRUE	FALSE
-PT_EHE800JJ	7316-229	NA	BS_JXF8A2A6	1738	FALSE	FALSE
 PT_EJ8TKG2Z	7316-3571	BS_NMJPX8VQ	BS_GC3CH9TY	1901	FALSE	FALSE
 PT_FAQWD7GX	7316-2311	BS_CN7PB0DN	BS_GMDQK06Q	2195	FALSE	FALSE
 PT_GY0QSY4H	7316-1075	BS_FWCKP4X1	BS_JCPKYHKY	4406	TRUE	FALSE

analyses/molecular-subtyping-CRANIO/results/CRANIO_molecular_subtype.tsv

@@ -19,7 +19,6 @@ PT_BZKJR4GK	7316-561	BS_NTXHP7QR	6565	BS_EMMF4PZX	CRANIO, To be classified
 PT_CEWNZVKF	7316-124	BS_MWXDJFWW	3725	BS_PRR8K9GE	CRANIO, ADAM
 PT_E3Y5BBSF	7316-3071	BS_W8DA9AXT	1555	BS_RFMQ7T0T	CRANIO, ADAM
 PT_EC8R84NM	7316-341	BS_CXDKK6KS	1344	BS_7T1J3KET	CRANIO, ADAM
-PT_EHE800JJ	7316-229	NA	1738	BS_JXF8A2A6	CRANIO, To be classified
 PT_EJ8TKG2Z	7316-3571	BS_NMJPX8VQ	1901	BS_GC3CH9TY	CRANIO, To be classified
 PT_FAQWD7GX	7316-2311	BS_CN7PB0DN	2195	BS_GMDQK06Q	CRANIO, To be classified
 PT_GY0QSY4H	7316-1075	BS_FWCKP4X1	4406	BS_JCPKYHKY	CRANIO, ADAM

analyses/molecular-subtyping-EPN/03-subgrouping_samples.html

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analyses/molecular-subtyping-EWS/01-run-subtyping-ewings.nb.html

@@ -1949,7 +1949,7 @@ <h3>List which samples are molecular_subtype == “EWS” or “EWS, To be class
 <!-- rnb-source-end -->
 <div data-pagedtable="false">
 <script data-pagedtable-source type="application/json">
-{"columns":[{"label":["Kids_First_Participant_ID"],"name":[1],"type":["chr"],"align":["left"]},{"label":["Kids_First_Biospecimen_ID_RNA"],"name":[2],"type":["chr"],"align":["left"]},{"label":["Kids_First_Biospecimen_ID_DNA"],"name":[3],"type":["chr"],"align":["left"]},{"label":["sample_id"],"name":[4],"type":["chr"],"align":["left"]},{"label":["molecular_subtype"],"name":[5],"type":["chr"],"align":["left"]}],"data":[{"1":"PT_VHS5RM2K","2":"BS_0448A413","3":"BS_FNM4BB83","4":"7316-364","5":"EWS"},{"1":"PT_HJMP6PH2","2":"BS_1021ZGQT","3":"BS_9SVMVJ45","4":"7316-3775","5":"EWS"},{"1":"PT_X8S0H6TG","2":"BS_1N9XZXGE","3":"BS_ZECKZTFC","4":"7316-876","5":"EWS"},{"1":"PT_SA94083W","2":"BS_8S86CM61","3":"NA","4":"7316-1856","5":"EWS"},{"1":"PT_J50NZYZF","2":"BS_B9V8RGTA","3":"BS_MWZCP1XW","4":"7316-956","5":"EWS"},{"1":"PT_F822DBA0","2":"BS_JFEZA9KE","3":"BS_KPWRDRFP","4":"7316-458","5":"EWS"},{"1":"PT_EHE800JJ","2":"BS_JXF8A2A6","3":"NA","4":"7316-229","5":"EWS"},{"1":"PT_J50NZYZF","2":"BS_PSNBFWQV","3":"BS_J52D4XQY","4":"7316-128","5":"EWS"},{"1":"PT_NBSRQAMS","2":"BS_R4Y180DM","3":"BS_Q9NHTR7G","4":"7316-1079","5":"EWS"},{"1":"PT_PJFTMJ6H","2":"BS_WJGFDRWK","3":"BS_SSYNTXDC","4":"7316-2150","5":"EWS"},{"1":"PT_HJMP6PH2","2":"BS_XZTV0J8W","3":"BS_XKM2EAT4","4":"7316-185","5":"EWS"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
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analyses/molecular-subtyping-EWS/results/EWS_results.tsv

@@ -5,7 +5,6 @@ PT_X8S0H6TG	BS_1N9XZXGE	BS_ZECKZTFC	7316-876	EWS
 PT_SA94083W	BS_8S86CM61	NA	7316-1856	EWS
 PT_J50NZYZF	BS_B9V8RGTA	BS_MWZCP1XW	7316-956	EWS
 PT_F822DBA0	BS_JFEZA9KE	BS_KPWRDRFP	7316-458	EWS
-PT_EHE800JJ	BS_JXF8A2A6	NA	7316-229	EWS
 PT_J50NZYZF	BS_PSNBFWQV	BS_J52D4XQY	7316-128	EWS
 PT_NBSRQAMS	BS_R4Y180DM	BS_Q9NHTR7G	7316-1079	EWS
 PT_PJFTMJ6H	BS_WJGFDRWK	BS_SSYNTXDC	7316-2150	EWS

analyses/molecular-subtyping-HGG/02-HGG-molecular-subtyping-subset-files.R

@@ -227,7 +227,7 @@ fusion_df <- fusion_df %>%
   left_join(select_metadata,
             by = c("Sample" = "Kids_First_Biospecimen_ID")) %>%
   filter(Sample %in% hgg_metadata_df$Kids_First_Biospecimen_ID) %>%
-  arrange(Kids_First_Participant_ID, sample_id)
+  arrange(Sample, FusionName)
 
 # Write to file
 write_tsv(fusion_df, file.path(subset_dir, "hgg_fusion.tsv"))

analyses/molecular-subtyping-HGG/03-HGG-molecular-subtyping-cnv.nb.html

@@ -3061,7 +3061,7 @@ <h4>Inclusion Criteria</h4>
 <!-- rnb-output-end -->
 <!-- rnb-chunk-end -->
 <!-- rnb-text-begin -->
-<p>We’d then expect 140 samples to have non-NA values in the cleaned CNV files.</p>
+<p>We’d then expect 141 samples to have non-NA values in the cleaned CNV files.</p>
 </div>
 <div id="read-in-cn-data" class="section level4">
 <h4>Read in CN Data</h4>
@@ -3233,8 +3233,8 @@ <h2>Join Together</h2>
 <!-- rnb-source-begin eyJkYXRhIjoibnJvdyhmaW5hbF9oZ2dfY25fZGYpIn0= -->
 <pre class="r"><code>nrow(final_hgg_cn_df)</code></pre>
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-<pre><code>[1] 140</code></pre>
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+<pre><code>[1] 141</code></pre>
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