Search results
Results from the WOW.Com Content Network
DESeq2 employs statistical methods to normalize and analyze RNA-seq data, making it a valuable tool for researchers studying gene expression patterns and regulation. It is available through the Bioconductor repository. It was first presented in 2014. [1] As of September 2023, its use has been cited over 30,000 times. [2]
Within computational biology, an MA plot is an application of a Bland–Altman plot for visual representation of genomic data. The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values.
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.
8: thickEnd: End coordinates from which the annotation is no longer displayed in a thicker way on a graphical representation (e.g.: the stop codon of a gene) No 9: itemRgb: RGB value in the form R, G, B (e.g. 255,0,0) determining the display color of the annotation contained in the BED file No 10: blockCount
Feature scaling is a method used to normalize the range of independent variables or features of data. In data processing , it is also known as data normalization and is generally performed during the data preprocessing step.
A Canonical XML document is by definition an XML document that is in XML Canonical form, defined by The Canonical XML specification. Briefly, canonicalization removes whitespace within tags, uses particular character encodings, sorts namespace references and eliminates redundant ones, removes XML and DOCTYPE declarations, and transforms ...
A yearlong HuffPost investigation into the heroin treatment industry.
To quantile normalize two or more distributions to each other, without a reference distribution, sort as before, then set to the average (usually, arithmetic mean) of the distributions. So the highest value in all cases becomes the mean of the highest values, the second highest value becomes the mean of the second highest values, and so on.