Maftools: efficient and comprehensive analysis of somatic variants in cancer

Mayakonda, Anand; Lin, De; Assenov, Yassen; Plass, Christoph; Koeffler, H. Phillip

doi:10.1101/gr.239244.118

Cited by 3,088 publications

(2,609 citation statements)

References 63 publications

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“…The statistical analysis was done in R-studio and the mutation analysis and drawing were done with the maftools package [20]. If no special instructions were given, P < 0.05 was considered significant.…”

Section: Resultsmentioning

confidence: 99%

Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets

Chen

Liu

2019

Preprint

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This study was aimed to investigate the mutations in colorectal cancer (CRC) for recurrent neoantigen identification. A total of 1,779 samples with whole exome sequencing (WES) data were obtained from 7 published CRC cohorts. Common HLA genotypes were used to predict the probability of neoantigens at high frequency mutants in the dataset. Based on the WES data, we not only obtained the most comprehensive CRC mutation landscape so far, but also found 1550 mutation sites which could be identified in at least 5 or more patients, including KRAS G12D (8%), KRAS G12V (5.8%), PIK3CA E545K (3.5%), PIK3CA H1047R (2.5%) and BMPR2 N583Tfs*44 (2.8%). These mutations can also be recognized by multiple common HLA molecules as potential 'public' neoantigens. Many of these mutations also have high mutation rates in metastatic pan-cancers, suggesting their value as therapeutic targets in different cancer types. Overall, our analysis provides recurrent neoantigens as potential cancer immunotherapy targets.

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Section: Resultsmentioning

confidence: 99%

Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets

Chen

Liu

2019

Preprint

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“…The performance of SigProfilerMatrixGenerator was benchmarked amongst five commonly used packages: deconstructSigs [27], mafTools [28], SomaticSignatures [29], signeR [30], and Helmsman [31]. While some of these packages can perform various additional tasks (e.g., extraction/decomposition of mutational signatures), the benchmarking considered only the generation of mutational matrices.…”

Section: Resultsmentioning

confidence: 99%

SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events

Bergstrom¹,

Mahto³

et al. 2019

Preprint

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Background: Cancer genomes are peppered with somatic mutations imprinted by different mutational processes. The mutational pattern of a cancer genome can be used to identify and understand the etiology of the underlying mutational processes. A plethora of prior research has focused on examining mutational signatures and mutational patterns from single base substitutions and their immediate sequencing context. We recently demonstrated that further classification of small mutational events (including substitutions, insertions, deletions, and doublet substitutions) can be used to provide a deeper understanding of the mutational processes that have molded a cancer genome. However, there has been no standard tool that allows fast, accurate, and comprehensive classification for all types of small mutational events Results: Here, we present SigProfilerMatrixGenerator, a Python based tool designed for optimized exploration and visualization of mutational patterns for all types of small mutational events. SigProfilerMatrixGenerator produces thirteen distinct matrices by considering transcriptional strand bias of individual events and by incorporating distinct classifications for single base substitutions, doublet base substitutions, and small insertions and deletions. While the tool provides a comprehensive classification of mutations, SigProfilerMatrixGenerator is also faster and more memory efficient than existing tools that generate only a single matrix. Conclusions: SigProfilerMatrixGenerator provides a standardized method for classifying small mutational events that is both efficient and scalable to large datasets. In addition to extending the classification of single base substitutions, the tool is the first to provide support for classifying doublet base substitutions and small insertions and deletions. SigProfilerMatrixGenerator is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/.

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“…MSI status was determined using MSIPred . Image and mutational frequency analyses were conducted using Maftools …”

Section: Methodsmentioning

confidence: 99%

Mucinous adenocarcinoma of the colon and rectum: A genomic analysis

Reynolds

OʼConnell

Fichtner

et al. 2019

Journal of Surgical Oncology

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Background and Objectives Mucinous adenocarcinoma is a distinct subtype of colorectal cancer (CRC) with a worse prognosis when compared with non‐mucinous adenocarcinoma. The aim of this study was to compare somatic mutations and copy number alteration (CNA) between mucinous and non‐mucinous CRC. Methods Data from The Cancer Genome Atlas‐colon adenocarcinoma and rectum adenocarcinoma projects were utilized. Mucinous and non‐mucinous CRC were compared with regard to microsatellite status, overall mutation rate, the most frequently mutated genes, mutations in genes coding for mismatch repair (MMR) proteins and genes coding for mucin glycoproteins. CNA analysis and pathway analysis was undertaken. Results Mucinous CRC was more likely to be microsatellite instability‐high (MSI‐H) and hypermutated. When corrected for microsatellite status the single‐nucleotide variation and insertion‐deletion rate was similar between the two cohorts. Mucinous adenocarcinoma was more likely to have mutations in genes coding for MMR proteins and mucin glycoproteins. Pathway analysis revealed further differences between the two histological subtypes in the cell cycle, RTK‐RAS, transforming growth factor‐β, and TP53 pathways. Conclusions Mucinous CRC has some distinct genomic aberrations when compared with non‐mucinous adenocarcinoma, many of which are driven by the increased frequency of MSI‐H tumors. These genomic aberrations may play an important part in the difference seen in response to treatment and prognosis in mucinous adenocarcinoma.

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Maftools: efficient and comprehensive analysis of somatic variants in cancer

Cited by 3,088 publications

References 63 publications

Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets

Recurrent Neoantigens in Colorectal Cancer as Potential Immunotherapy Targets

SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events

Mucinous adenocarcinoma of the colon and rectum: A genomic analysis

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