BUSCADOR RECOLECTA

Gitools is a framework for analysis and visualization of multidimensional genomic data using interactive heat-maps.

Method to identify genomic regions, both coding and non-coding, bearing mutations with significant shift towards high functional impact across a cohort of tumos (FMbias), which are candidates to function as cancer drivers, through a local test.

The effects on growth performance of supplementation of four different AA combinations in a milk replacer (MR, 25.4% CP and 20.3% fat) based on skimmed milk powder and whey protein concentrate were evaluated in 76 Holstein male calves (3 ± 1.7 d old). The 4 MR were: CTRL with no AA supplementation; PG supplying additional 0.3% Pro and 0.1% Gly; FY supplying additional 0.2% Phe and 0.2% Tyr; KMT providing additional 0.62% Lys, 0.22% Met, and 0.61% Thr. All calves were fed the same milk allowance program and were weaned at 56 d of study. Concentrate intake was limited to minimize interference of potential differences in solid feed intake among treatments. Animals were weighed weekly, intakes recorded daily, and blood samples obtained at 2, 5, and 7 wk of study to determine serum urea and plasma AA concentrations. The file presents data of calf performance. Data was collected at Torre Marimon IRTA calf facilities (Caldes de Montbui, Spain) during 2017.

Python tab files parsing and validating schema tools.

A needle-plot (aka stem-plot or lollipop-plot) plots each data point as a big dot and adds a vertical line that makes it appear like a needle.

OncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that mutations in these regions change the function of these proteins in a manner that provides an adaptive advantage to cancer cells and consequently are positively selected during clonal evolution of tumours, and this property can thus be used to nominate novel candidate driver genes./nThe method does not assume that the baseline mutation probability is homogeneous across all gene positions but it creates a background model using silent mutations. Coding silent mutations are supposed to be under no positive selection and may reflect the baseline clustering of somatic mutations. Given recent evidences of non-random mutation processes along the genome, the assumption of homogenous mutation probabilities is likely an oversimplication introducing bias in the detection of meaningful events.

OncodriveFM detects candidate cancer driver genes and pathways from catalogs of somatic mutations in a cohort of tumors by computing the bias towards the accumulation of functional mutations (FM bias).This novel approach avoids some known limitations of recurrence-based approaches, such as the dif?culty to estimate background mutation rate, and the fact that they usually fail to identify lowly recurrently mutated driver genes.

Onexus is a modular framework to manage the complete life cycle of data analyses. Data analyses follow these steps: analysis definition, analysis execution, results storing, results browsing and finally results publishing.

Wok is a workflow management system implemented in Python that makes very easy to structure the workflows, parallelize their execution and monitor its progress among other things. It is designed in a modular way allowing to adapt it to different infraestructures./nFor the time being it is strongly focused on clusters implementing any DRMAA compatible resource manager (i.e. Oracle Grid Engine) which working nodes have a shared folder in common. Other, more flexible infrastructures (such as the Amazon EC2) are considered for future implementations.

Machine-learning based approach to classify cancer driver genes into to Activating or Loss of Function roles for cancer gene development.