Data files used for exploring BRAF mutation-associated gene risk model for predicting the prognosis of melanoma (dataset)

Data files used for exploring BRAF mutation-associated gene risk model for predicting the prognosis of melanoma

The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21532917

Datacite citation style:

Xiang Huang (2022): Data files used for exploring BRAF mutation-associated gene risk model for predicting the prognosis of melanoma. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21532917.v1

Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

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categories

Genetics

keywords

BRAF mutations, immune checkpoint, melanoma,, prediction model, prognosis

licence

CC BY 4.0

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by Xiang Huang

We identified significantly enriched KEGG pathways and corresponding genes in the BRAF mutant group via GSEA. For the first time, a prognostic signature based on seven BRAF-related genes with an independent prognostic value for melanoma patients and related to immune cell infiltration and checkpoint was constructed and validated. Furthermore, we established a nomogram based on the prognostic signature and independent clinical characteristics, providing a tool for the objective assessment of the survival rate of melanoma patients.

history

2022-11-14 first online, published, posted

publisher

4TU.ResearchData

format

*.gmt; .txt; *.tsv; *.xlsx

organizations

Guizhou Medical University

DATA

files (32)

3,036 bytesMD5:d0dfa29d8ef81292d76866c34b1d30ac fig.2-Group-BRAF.cls.txt
21,094 bytesMD5:c6e7c22a25e241a2e9243550db18e253 fig.2-gsea_report_for_MUT_1663369829866.tsv
6,316 bytesMD5:24607071e4fb72c5d32a0cb50761d1ed fig.2-gsea_report_for_WILD_1663369829866.tsv
89,517 bytesMD5:a2c8ba8056e10dd40ccd8b6fe73acc1c fig.2-KEGG-gene-sets.gmt
733,979 bytesMD5:74865529b02a625f60e400945ceb97e8 fig.2-ranked_gene_list_MUT_versus_WILD_1663369829866.tsv
151,206,608 bytesMD5:3780ac84229defd0016a9689f865e901 fig.2-total-exp.gct.txt
64,441 bytesMD5:b0a9d9f874ebc448e13215a56387a152 fig.3-Lasso-Gene-list2.txt
18,598 bytesMD5:d0fab5a4525d2fc335247e122b12ac72 fig.3-Lasso-riskscore.txt
6,678 bytesMD5:63f0db1d4a9b92e77d194d0f0baa7a78 fig.3-univariate result.txt
319,730 bytesMD5:abbf7c6015e76ca9529f817c61d3a72b fig.3-univariate-Gene-list.txt
10,741 bytesMD5:7dfe85d7d828b2cabddf7084c24430c8 fig.3-univariate-survival.tsv
128,199 bytesMD5:5fd90009499d745c17a990aa9d399aca fig.4-ICGC-data-heat map.xlsx
27,761 bytesMD5:070552601b39765673c124816666f9aa fig.4-ICGC-data-KM.xlsx
83,783 bytesMD5:150c1d9ee3180f0ee16c50aa53f341f1 fig.4-ICGC-data-ROC.xlsx
66,779 bytesMD5:d4bd7e7ca6b4ea23ccc8b27c70e18afc fig.4-TCGA-data-heat map.xlsx
18,573 bytesMD5:6b96f9094e0bf9cbfda9df74cffca75c fig.4-TCGA-data-KM.txt
18,400 bytesMD5:8030ab8b1192d06f4926c2b26a9b0db8 fig.4-TCGA-data-ROC.txt
34,683 bytesMD5:e11e45c525d0b6c73568617675b86369 fig.5-data.xlsx
100,209 bytesMD5:fd47a0f62e40002b64fa146d5112b907 fig.6-data.xlsx
18,400 bytesMD5:8030ab8b1192d06f4926c2b26a9b0db8 fig.6-riskscore.txt
401,578 bytesMD5:9f6ac951602796475092ac9bce6d44df fig.6-TCGA-SKCM.GDC_phenotype.tsv
18,500 bytesMD5:d5fe2732b69016c8a98be377ac20fff1 fig.7-nomagram.txt
22,194 bytesMD5:be4d8e4d7773f018a3b29db790f8ed8e fig.7-TCGA-SKCM-clinical.tsv
10,741 bytesMD5:7dfe85d7d828b2cabddf7084c24430c8 fig.7-TCGA-SKCM.survival.tsv
145,986,200 bytesMD5:ead22d184b6f9226a205f559b0557273 fig.8-FPKM-Non-nor.txt
36,987 bytesMD5:db3ddfecfe0f5d46cc61e811bc358c4c fig.8-Group-riskscore.xlsx
50,523 bytesMD5:e6e004d82c2a0b21b730d3cb08a09abb fig.8-gsea_report_for_risk_high_1664072176472.tsv
681,128 bytesMD5:26bd4a557787c5ac77aaf5d6ec2ba7f1 fig.8-gsea_report_for_risk_low_1664072176472.tsv
733,471 bytesMD5:34126a89278f8fdadbd691b3c22ee9a9 fig.8-ranked_gene_list_risk_high_versus_risk_low_1664072176472.tsv
151,206,608 bytesMD5:3780ac84229defd0016a9689f865e901 fig.8-total-exp.gct.txt
294,229 bytesMD5:857ef930c5e35f6747416d122bc71f07 fig.9-immueScore.xlsx
68,648 bytesMD5:3d1680273d5020bf574dc119655e3c0d fig.9-immune checkpoints.xlsx
download all files (zip)
452,488,332 bytes unzipped