Search Results for "data leakage detection python"

A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis.

An update to Python package to perform comprehensive analysis of small RNA sequencing data, including miRNA annotation, A-to-I editing, novel miRNA detection, isomiR analysis, visualization through IGV, processing Unique Molecular Identifieres (UMI), tRF detection and producing interactive graphical output. miRge3.0 is developed in python v3.8 and is a recent update of our previous version miRge2.0.

FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples. The aims of FusionCatcher are: - very good detection rate for finding candidate fusion genes, - very easy to use (i.e. no a priori knowledge of databases and bioinformatics is needed in order to run FusionCatcher), - very good detection of challenging fusion genes, like for example IGH...

TCellXTalk is a comprehensive database of experimentally detected phosphorylation, ubiquitination and acetylation sites in human T cells. The web-app at www.TCellXTalk.org makes TCellXTalk accessible from Internet, and enables the in silico prediction of potential co-modified peptides to facilitate their experimental detection, using targeted or directed mass spectrometry, for the study of protein post-translational modification cross-talk. More detailed information on TCellXTalk and...

REDItools are python scripts developed with the aim to study RNA editing at genomic scale by next generation sequencing data. RNA editing is a post-transcriptional phenomenon involving the insertion/deletion or substitution of specific bases in precise RNA localizations. In human, RNA editing occurs by deamination of cytosine to uridine (C-to-U) or mostly by the adenosine to inosine (A-to-I) conversion through ADAR enzymes. A-to-I substitutions may have profound functional consequences and...

Copy Number Analysis for Targeted Resequencing (CONTRA) is a tool for copy number variation (CNV) detection for targeted resequencing data such as those from whole-exome capture data.

During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community,...

This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...

Aberration Detection in Tumour Exome (ADTEx) is a tool for copy number variation (CNV) detection for whole-exome data from paired tumour/matched normal samples.

FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts.

This software detects homologous recombination events (HREs) from SNP data. Based on SNP alleles calls and locations, it breaks the genomes into locally colinear blocks, and looks for cases where SNPs do not agree with the vertical pattern of inheritance in a phylogeny. It applies a dynamic programming algorithm to model whether changes within a block are likely a result of mutations, sequencing errors, or HRE. We use information from the nearby SNPs, so that if 1-2 alleles in a series of...

This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs the following files: .fet.n (feature file) .mask.n (needed for using the new (masked) KlustaKwik) .clu.n (a trivial clue file where everything is put into a single cluster) .fmask.n (trial - float masks instead of binary, we are using this for testing masked KlustaKwik) .spk.n (spike file) .upsk.n (unfiltered spike waveform) .res.n (list of spike times) .xml (an xml file with all the parameters that can subsequently be used by neuroscope or klusters) .fil (highpass filtered data) .h5 (

This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.

The RDXplorer is a computational tool for copy number variants (CNV) detection in whole human genome sequence data using read depth (RD) coverage. CNV detection is based on the Event-Wise Testing (EWT) algorithm recently published by our group.