Comparison of microbiome samples: methods and computational challenges
The study of microbial communities crucially relies on the comparison of metagenomic next-
generation sequencing data sets, for which several methods have been designed in recent …
generation sequencing data sets, for which several methods have been designed in recent …
K2mem: discovering discriminative k-mers from sequencing data for metagenomic reads classification
D Storato, M Comin - IEEE/ACM Transactions on Computational …, 2021 - ieeexplore.ieee.org
The major problem when analyzing a metagenomic sample is to taxonomically annotate its
reads to identify the species they contain. Most of the methods currently available focus on …
reads to identify the species they contain. Most of the methods currently available focus on …
Classgraph: improving metagenomic read classification with overlap graphs
M Cavattoni, M Comin - Journal of Computational Biology, 2023 - liebertpub.com
Current technologies allow the sequencing of microbial communities directly from the
environment without prior culturing. One of the major problems when analyzing a microbial …
environment without prior culturing. One of the major problems when analyzing a microbial …
Metaprob 2: metagenomic reads binning based on assembly using minimizers and k-mers statistics
Current technologies allow the sequencing of microbial communities directly from the
environment without prior culturing. One of the major problems when analyzing a microbial …
environment without prior culturing. One of the major problems when analyzing a microbial …
[PDF][PDF] Efficient k-mer Indexing with Application to Map**-free SNP Genoty**.
Advances in sequencing technologies and computational methods have enabled rapid and
accurate identification of genetic variants. Accurate genotype calls and allele frequency …
accurate identification of genetic variants. Accurate genotype calls and allele frequency …
MetaCon: unsupervised clustering of metagenomic contigs with probabilistic k-mers statistics and coverage
Motivation Sequencing technologies allow the sequencing of microbial communities directly
from the environment without prior culturing. Because assembly typically produces only …
from the environment without prior culturing. Because assembly typically produces only …
MetaConClust-unsupervised binning of metagenomics data using consensus clustering
Background: Binning of metagenomic reads is an active area of research, and many
unsupervised machine learning-based techniques have been used for taxonomic …
unsupervised machine learning-based techniques have been used for taxonomic …
Better quality score compression through sequence-based quality smoothing
Motivation Current NGS techniques are becoming exponentially cheaper. As a result, there
is an exponential growth of genomic data unfortunately not followed by an exponential …
is an exponential growth of genomic data unfortunately not followed by an exponential …
Indexing k-mers in linear space for quality value compression
Many bioinformatics tools heavily rely on k-mer dictionaries to describe the composition of
sequences and allow for faster reference-free algorithms or look-ups. Unfortunately, naive k …
sequences and allow for faster reference-free algorithms or look-ups. Unfortunately, naive k …
Improving metagenomic classification using discriminative k-mers from sequencing data
D Storato, M Comin - … 16th International Symposium, ISBRA 2020, Moscow …, 2020 - Springer
The major problem when analyzing a metagenomic sample is to taxonomically annotate its
reads to identify the species they contain. Most of the methods currently available focus on …
reads to identify the species they contain. Most of the methods currently available focus on …