From 5225601474b54b437e7900d7c61f8c40802e9a36 Mon Sep 17 00:00:00 2001 From: Miguel Brown Date: Wed, 14 Jun 2023 13:29:31 -0400 Subject: [PATCH] :pencil: created config for teachey --- STUDY_CONFIGS/tll_sd_aq9kvn5p_2019_case_meta_config.json | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/STUDY_CONFIGS/tll_sd_aq9kvn5p_2019_case_meta_config.json b/STUDY_CONFIGS/tll_sd_aq9kvn5p_2019_case_meta_config.json index b2e1c4b..ec418c4 100644 --- a/STUDY_CONFIGS/tll_sd_aq9kvn5p_2019_case_meta_config.json +++ b/STUDY_CONFIGS/tll_sd_aq9kvn5p_2019_case_meta_config.json @@ -166,10 +166,10 @@ }, "study": { "_comment": "see https://docs.cbioportal.org/5.1-data-loading/data-loading/file-formats#cancer-study for detailed specifics", - "description": "This study focuses on improving the treatment of relapsed T-cell acute lymphoblastic leukemia (T-ALL), a type of blood cancer with a poor prognosis. Currently, it is challenging to identify patients at high risk of relapse at the time of diagnosis. The study analyzes the genetic makeup of T-ALL patients from a clinical trial (AALL0434) to find genetic alterations that could help predict poor outcomes and guide alternative treatments. The research uses comprehensive genomic profiling techniques like RNA sequencing, DNA CNV analysis, WXS, and WGS. The specific goals are to identify recurrent genetic alterations associated with poor prognosis, discover novel genetic changes, and find germline genetic variants that make patients more susceptible to T-ALL and increased chemotherapy toxicity. The findings aim to advance our understanding of T-ALL and provide insights for better risk stratification and personalized therapies. Added keywords: KF, GMKF. For updates, please see here: Release Notes", + "description": "This study focuses on improving the treatment of relapsed T-cell acute lymphoblastic leukemia (T-ALL), a type of blood cancer with a poor prognosis. Currently, it is challenging to identify patients at high risk of relapse at the time of diagnosis. The study analyzes the genetic makeup of T-ALL patients from a clinical trial (AALL0434) to find genetic alterations that could help predict poor outcomes and guide alternative treatments. The research uses comprehensive genomic profiling techniques like RNA sequencing, DNA CNV analysis, WXS, and WGS. The specific goals are to identify recurrent genetic alterations associated with poor prognosis, discover novel genetic changes, and find germline genetic variants that make patients more susceptible to T-ALL and increased chemotherapy toxicity. The findings aim to advance our understanding of T-ALL and provide insights for better risk stratification and personalized therapies. KF, GMKF. For updates, please see here: Release Notes", "groups": "PUBLIC", "cancer_study_identifier": "tll_sd_aq9kvn5p_2019", - "type_of_cancer": "brain", + "type_of_cancer": "tll", "short_name": "tll_sd_aq9kvn5p_2019", "reference_genome": "hg38", "display_name": "Kids First: Comprehensive Genomic Profiling to Improve Prediction of Clinical Outcome for Children with T-cell Acute Lymphoblastic Leukemia (phs002276, Provisional)" @@ -219,7 +219,7 @@ "database_pulls": { "_comment": "This section is used to numerate relevant database schema and tables needed for clinical data and supporting genomic etl files", "manifests": { - "mioncoseq": { + "tll_sd_aq9kvn5p_2019": { "table": "bix_genomics_file.sd_aq9kvn5p-genomics_file_manifest", "file_type": ["RSEM_gene","annofuse_filtered_fusions_tsv","annotated_public_outputs","ctrlfreec_pval","ctrlfreec_info","ctrlfreec_bam_seg"], "out_file": "tll_sd_aq9kvn5p_2019_genomics_file_manifest.txt"