Package 'SingscoreAMLMutations'

Title: Using singscore to predict mutations in AML from transcriptomic signatures
Description: This workflow package shows how transcriptomic signatures can be used to infer phenotypes. The workflow begins by showing how the TCGA AML transcriptomic data can be downloaded and processed using the TCGAbiolinks packages. It then shows how samples can be scored using the singscore package and signatures from the MSigDB. Finally, the predictive capacity of scores in the context of predicting a specific mutation in AML is shown.The workflow exhibits the interplay of Bioconductor packages to achieve a gene-set level analysis.
Authors: Dharmesh D. Bhuva [aut, cre] (ORCID: <https://orcid.org/0000-0002-6398-9157>), Momeneh Foroutan [aut] (ORCID: <https://orcid.org/0000-0002-1440-0457>), Yi Xie [aut] (ORCID: <https://orcid.org/0000-0002-1938-4089>), Ruqian Lyu [aut], Malvika Kharbanda [aut] (ORCID: <https://orcid.org/0000-0001-9726-3023>), Joseph Cursons [aut] (ORCID: <https://orcid.org/0000-0002-5053-4540>), Melissa J. Davis [aut] (ORCID: <https://orcid.org/0000-0003-4864-7033>)
Maintainer: Dharmesh D. Bhuva <[email protected]>
License: Artistic-2.0
Version: 1.28.0
Built: 2026-10-04 17:16:31 UTC
Source: https://github.com/bioc/SingscoreAMLMutations

Help Index

SingscoreAMLMutations: Using singscore to predict mutations in AML from transcriptomic signatures

Description

This workflow package shows how transcriptomic signatures can be used to infer phenotypes. The workflow begins by showing how the TCGA AML transcriptomic data can be downloaded and processed using the TCGAbiolinks packages. It then shows how samples can be scored using the singscore package and signatures from the MSigDB. Finally, the predictive capacity of scores in the context of predicting a specific mutation in AML is shown.The workflow exhibits the interplay of Bioconductor packages to achieve a gene-set level analysis.

Author(s)

Maintainer: Dharmesh D. Bhuva [email protected] (ORCID)

Authors:

See Also

Useful links:

Mutation data for 4 genes for the TCGA AML patients

Description

This is the processed version of the mutation data available from the TCGA AML patients. The data set

Usage

AMLPatientMutationsTCGA

Format

A data.frame with 151 samples (rows) and mutation annotations for 4 genes:

NPM1c.Mut

Mutations in the *NPM1* gene that result in a frame shit, also known as the NPM1c mutation (TRUE if mutated)

KMT2A.Fusion

Fusion products of the *KMT2A* gene, also commonly known as *MLL* (TRUE if a fusion product exists)

KMT2A.PTD

Partial tandem duplication of the *KMT2A* gene (TRUE if PTD observed)

PML.RARA

Fusion of the *PML* and *RARA* gene (TRUE for fusions)

Source

(https://tcga-data.nci.nih.gov/docs/publications/aml_2012/SupplementalTable01.xlsx)

References

Cancer Genome Atlas Research Network, 2013. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. New England Journal of Medicine, 368(22), pp.2059-2074.

Examples

data(AMLPatientMutationsTCGA)