{kmers} R# Documentation

kmers


require(GCModeller);

{$desc_comments}
imports "kmers" from "metagenomics_kit";

.NET clr type export
kmer: KmerSeed
kmer_bloom: KmerBloomFilter

kmer bloom filter of a specific genome



.NET clr function exports
as.data.frame.bracken Bracken:

the bracken abundance table

as.data.frame.sequencesource SequenceSource:

source information of the target genome source sequence

as.data.frame.krakenoutputrecord KrakenOutputRecord:

用于存储 --output 文件中每一行的数据,这个文件详细列出了每一条序列(read)的分类结果。每一行对应一条 read。

as.data.frame.sequencehit SequenceHit:
write.kmers_background
read.kmers_background
bayes_background
read_seqid
bloom_filters
bloom_vector
make_vector

make vector embedding

make_classify

just make reads classify of the fastq reads based on the k-mer distribution

benchmark
MAG_classify
bayes_estimate
bayes_abundance

quantify of the metagenome community via kmers and bayes method

as.bloom_filter

cast the genomics sequence as kmer based bloom filter model

parse_kraken_output

Parse the reads annotation result generated from the kraken2

make_seq_groups
parse_kraken_report
read.kraken2
read_brackens
read.kraken2_reads

read reads annotation result generated from the kraken2

hits_matrix
filter_classification

filter the reads data that has the specific taxonomy id assignment.

filter_hostId
kraken_data

extract the kraken2 quantify result data

filter_reads

usually be apply for host removal

seq_info
taxonomy_expression
kraken_seqs

extract gene/genomics sequences from genbank file for kraken2 sequence classification


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