Search results
Results from the WOW.Com Content Network
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.
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.
The following is a Python implementation of BatchNorm for 2D convolutions: import numpy as np def batchnorm_cnn ( x , gamma , beta , epsilon = 1e-9 ): # Calculate the mean and variance for each channel. mean = np . mean ( x , axis = ( 0 , 1 , 2 ), keepdims = True ) var = np . var ( x , axis = ( 0 , 1 , 2 ), keepdims = True ) # Normalize the ...
An object a is strongly normalizing if every sequence of rewrites starting from a eventually terminates with a normal form. An abstract rewriting system is strongly normalizing , terminating , noetherian , or has the (strong) normalization property (SN), if each of its objects is strongly normalizing.
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.
If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle 1259 ahead. Let's start with a few hints.
It is common practice in some disciplines (e.g. statistics and time series analysis) to normalize the cross-correlation function to get a time-dependent Pearson correlation coefficient. However, in other disciplines (e.g. engineering) the normalization is usually dropped and the terms "cross-correlation" and "cross-covariance" are used ...