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k-mer - Wikipedia k -mers are simply length subsequences For example, all the possible k -mers of a DNA sequence are shown below: An example 8-mer spectrum for E coli comparing 8-mers' frequency (i e multiplicities) with their number of occurrences
k-mer counting, part I: Introduction | BioInfoLogics Checking the phiX hist histogram (A K A kmer spectrum) file, every 27-mer in the genome appears only once After the header lines starting with #, every line has a copy number (A K A frequency) and a number of k-mers
Kmers def kmer_count(k, seq): ''' Return a list of the number of times each possible k-mer appears in seq, including overlapping occurrences ''' mers = generate_dna_kmers(k) rv = [] for m in mers: cnt = count_mer(m, seq) if cnt != 0: rv append((m, cnt)) return rv
Bioinformatics 1: K-mer Counting - Medium K-mer counting is an interesting yet challenging problem in bioinformatics In this article, we’ll talk about what k-mers are, the problem of k-mer counting, its applications, and some
Guide to k-mer approaches for genomics across the tree of life The wide array of currently available genomes display a wonderful diversity in size, composition and structure with many more to come thanks to several global biodiversity genomics initiatives starting in recent years However, sequencing of genomes, even with all the recent advances, can still be challenging for both technical (e g small physical size, contaminated samples, or access to
UCD Bioinformatics Core Workshop - GitHub Pages Extremely large (haploid size »10GB) and or very repetitive genomes may benefit from larger kmer lengths to increase the number of unique k-mers Genome copies
De Novo DNA Sequencing and the Special k-mer - Bitesize Bio De novo DNA sequencing is the new standard in molecular biology But how does one really decipher the actual sequence from random reads Learn more about the K-mer in this article
KmerGO: A Tool to Identify Group-Specific Sequences With Based on long k -mers (k > 21), Mash (Ondov et al , 2016), Skmer (Sarmashghi et al , 2019), and Kmer-db (Deorowicz et al , 2018) use MinHash to approximate Jaccard distance between pairwise sequences based on randomly sampled small set of k -mers
A survey of k-mer methods and applications in bioinformatics Kmer-db is an efficient tool for estimating evolutionary relationships between pathogens based on derived k-mers [121] This makes it well-suited for processing large and diverse bacterial genome datasets, enabling more accurate comparisons for phylogeny reconstruction even among distantly related genomes with limited shared k-mers