Cancer is one of the leading causes of mortality worldwide. Breast cancer is the most frequent cancer in women, and in recent years it has become a serious public health problem in Colombia. The development of large-scale omic techniques allows simultaneous analysis of all active genes in tumor cells versus normal cells, providing new ways to discover the drivers of malignant transformations. Whole exome sequencing (WES) was obtained to provide a deep view of the mutational genomic profile in a set of cancer samples from Southwest Colombian women. WES was performed on 52 tumor samples from patients diagnosed with invasive breast cancer, which in most cases (33/52) were ductal luminal breast carcinomas (IDC-LM-BRCA). Global variant call was calculated, and six different algorithms were applied to filter out false positives and identify pathogenic variants. To compare and expand the somatic tumor variants found in the Colombian cohort, exome mutations and genome-wide expression alterations were detected in a larger set of tumor samples of the same breast cancer subtype from TCGA (that included DNA-seq and RNA-seq data). Genes with significant changes in both the mutational and expression profiles were identified, providing a set of genes and mutations associated with the etiology of ductal luminal breast cancer. This set included 19 single mutations identified as tumor driver mutations in 17 genes. Some of the genes (ATM, ERBB3, ESR1, TP53) are well-known cancer genes, while others (CBLB, PRPF8) presented driver mutations that had not been reported before. In the case of the CBLB gene, several mutations were identified in TCGA IDC-LM-BRCA samples associated with overexpression of this gene and repression of tumor suppressive activity of TGF-β pathway.

Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scripts and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies.

Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scripts and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies.

Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scrips and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies.

Bioinformatics is an interdisciplinary field that develops software methods and tools to understand biological data. Actually, in branches such as genomics, there are a large number of software tools that serve to support different processes such as genetic data sequencing, genomes, biotechnological applications, among other activities, which contribute knowledge to different fields of study such as environment, medicine, energy and others. As a support to the area of genomics and specifically to the field of genomics, we describe and propose a method based on mining software repositories (MSR), which monitors, evaluates and maps the genomic software hosted in the GitHub. We use the VigHub tool to extract meta-data from projects and create visualizations on technological maps. We present a detailed systematic review of the genomic software projects on GitHub, where the highlights of the genomics area are shown. Specifically we show the technological maps of the programming languages most used in the creation of software. The Time-line, where software projects are displayed by category, relevance and programming languages as a function of time. Classification of the repositories by software categories and the most successful genomic software repositories in GitHub according to stars and score. This paper is aimed at bioinformatics researchers that require relevant information about the current state of a specific genomic technology found in GitHub. The method facilitates the identification of ideas, source code, specific data, platforms, applications, scripts and tools that support research and innovation in genomic software projects. The analysis provided in this paper allowed to identify software trends in the area, as well as new perspectives and future technologies.