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DESeq2 is a software package in the field of bioinformatics and computational biology for the statistical programming language R. It is primarily employed for the analysis of high-throughput RNA sequencing (RNA-seq) data to identify differentially expressed genes between different experimental conditions.
fastqp Simple FASTQ quality assessment using Python. Kraken: [9] A set of tools for quality control and analysis of high-throughput sequence data. HTSeq [10] The Python script htseq-qa takes a file with sequencing reads (either raw or aligned reads) and produces a PDF file with useful plots to assess the technical quality of a run.
It is possible to use histogram matching to balance detector responses as a relative detector calibration technique. It can be used to normalize two images, when the images were acquired at the same local illumination (such as shadows) over the same location, but by different sensors, atmospheric conditions or global illumination.
The document is encoded in UTF-8; Line breaks normalized to #xA on input, before parsing; Attribute values are normalized, as if by a validating processor; Character and parsed entity references are replaced; CDATA sections are replaced with their character content; The XML declaration and document type declaration are removed
The list of wasteful taxpayer spending is compiled each year by the Beacon Center, a nonprofit that provides free market solutions to public policy issues in the state. In Memphis, a report by ...
This software analyzes differential quantification data and is assisted by tools and visualization options. It is possible to process label-free and tandem mass-tagged data. [83] pymzML Open source: Python module to interface mzML data in Python, based on cElementTree with additional tools for MS-informatics. [84] Pyteomics Open source
Average mortgage rates tick lower across popular terms as of Tuesday, December 17, 2024, with the Federal Reserve set to begin its final rate-setting session of the year.Traders expect the Fed ...
In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...