![]() Classification of the remaining reads is then accomplished by using KrakenUniq 3 and Kraken2Uniq. For removal of host DNA, one can use Bowtie 2 7 (also developed by some of the authors of this protocol) as a fast, sensitive aligner that can compare sequencing reads to the human reference genome. ![]() The second and third steps are essentially the same as those done for microbiome experiments, while the first and last steps are needed to ensure the accuracy of any pathogen that is identified. Pathogen identification studies conceptually include the following steps: (1) removal of host DNA from the microbial reads (2) classification of the remaining microbial reads (3) comparison of sample reads against control samples and (4) validation of pathogen classifications. In pathogen identification experiments, researchers and clinicians are interested in identifying pathogenic microbes that might be the cause of a harmful infection. ![]() Finally, KrakenTools and Pavian 6 provide a comprehensive set of tools for downstream statistical analysis and visualization of the classification and abundance estimation results. Bracken 5 was developed to work in conjunction with Kraken to compute species abundance using Kraken classification results. Kraken 2 and Kraken 2 4 (an improved version of Kraken) were previously developed by some of us for rapid, accurate classification of sequencing reads. Following characterization of the original data, downstream analyses may include (4) statistical methods for comparing the microbial compositions of different environments or (5) visualization methods for understanding microbial compositions. However, many studies prefer to analyze all of the sequencing reads collected from a sample, which is the strategy we focus on in this protocol. The most widely used marker gene is ribosomal RNA, but protein-coding genes can also be used, particularly those that are expected to be present in exactly one copy per cell. When computing relative abundance, researchers sometimes focus on a limited number of “marker” genes, classifying only the reads that align within these genes. Microbiome experiments begin with (1) removing host DNA and then (2) classifying a set of sequencing reads, with each read assigned to a taxonomic category (species, genus, or higher-level taxa), followed by (3) computing the relative abundance of different species in the sample. These tools include Kraken 2, KrakenUniq 3, Kraken 2 4, Kraken2Uniq (based on KrakenUniq), Bracken 5, KrakenTools, and Pavian 6. The suite of tools in the Kraken package were developed to cover many of the bioinformatics needs of both microbiome and pathogen metagenomics experiments. In contrast, in a pathogen identification experiment, researchers focus on identifying one or a few pathogenic microbes, with the goal of diagnosing an infection. ![]() In microbiome experiments, researchers evaluate all of the microbial organisms identified in a given sample, often with the goal of describing what is present. ![]() Metagenomics experiments take many forms, two of which can be broadly categorized as either microbiome experiments or pathogen identification experiments. Metagenomics sequencing has greatly improved our understanding of the microscopic world by revealing a vast range of microbial organisms that were previously unobserved, many of which cannot be grown in laboratory cultures 1. ![]()
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