seqArchR: seqArchR: A package for de novo discovery of different...

In snikumbh/seqArchR: Identify Different Architectures of Sequence Elements

seqArchR: A package for de novo discovery of different sequence architectures

Description

Given a set of DNA sequences, seqArchR enables unsupervised discovery of _de novo_ clusters with characteristic sequence architectures characterized by position-specific motifs or composition of stretches of nucleotides, e.g., CG-richness, etc.

Call this function to process a data set using seqArchR.

Usage

seqArchR(
  config,
  seqs_ohe_mat,
  seqs_raw,
  seqs_pos = NULL,
  total_itr = NULL,
  set_ocollation = NULL,
  fresh = TRUE,
  use_oc = NULL,
  o_dir = NULL
)

Arguments

config	seqArchR configuration object as returned by set_config. This is a required argument.
seqs_ohe_mat	A matrix of one-hot encoded sequences with sequences along columns. This is a required argument.
seqs_raw	A DNAStringSet object. The FASTA sequences as a DNAStringSet object. This argument required argument.
seqs_pos	Vector. Specify the tick labels for sequence positions. Default is NULL.
total_itr	Numeric. Specify the number of iterations to perform. This should be greater than zero. Default is NULL.
set_ocollation	Logical vector. A logical vector of length 'total_itr' specifying for every iteration of seqArchR if collation of clusters from outer chunks should be performed. TRUE denotes clusters are collated, FALSE otherwise.
fresh	Logical. Specify if this is (not) a fresh run. Because seqArchR enables checkpointing, it is possible to perform additional iterations upon clusters from an existing seqArchR result (or a checkpoint) object. See 'use_oc' argument. For example, when processing a set of FASTA sequences, if an earlier call to seqArchR performed two iterations, and now you wish to perform a third, the arguments 'fresh' and 'use_oc' can be used. Simply set 'fresh' to FALSE and assign the sequence clusters from iteration two from the earlier result to 'use_oc'. As of v0.1.3, with this setting, seqArchR returns a new result object as if the additional iteration performed is the only iteration.
use_oc	List. Clusters to be further processed with seqArchR. These can be from a previous seqArchR result (in which case use get_seqs_clust_list function), or simply clusters from any other method. Warning: This has not been rigorously tested yet (v0.1.3).
o_dir	Character. Specify the output directory with its path. seqArchR will create this directory. If a directory with the given name exists at the given location, seqArchR will add a suffix to the directory name. This change is reported to the user. Default is NULL. When NULL, just the result is returned, and no plots or checkpoints or result is written to disk.

Details

The seqArchR package provides three categories of important functions: related to data preparation and manipulation, performing non-negative matrix factorization, performing clustering, and visualization-related functions.

Value

A nested list of elements as follows:

seqsClustLabels

A list with cluster labels for all sequences per iteration of seqArchR. The cluster labels as stored as characters.

clustBasisVectors

A list with information on NMF basis vectors per iteration of seqArchR. Per iteration, there are two variables 'nBasisVectors' storing the number of basis vectors after model selection, and 'basisVectors', a matrix storing the basis vectors themselves. Dimensions of the 'basisVectors' matrix are 4*L x nBasisVectors (mononucleotide case) or 16*L x nBasisVectors (dinucleotide case).

clustSol

The clustering solution obtained upon processing the raw clusters from the last iteration of seqArchR's result. This is handled internally by the function collate_seqArchR_result using the default setting of Euclidean distance and ward.D linkage hierarchical clustering.

rawSeqs

The input sequences as a DNAStringSet object.

timeInfo

Stores the time taken (in minutes) for processing each iteration. This element is added only if 'time' flag is set to TRUE in config.

config

The configuration used for processing.

call

The function call itself.

Functions for data preparation and manipulation

• prepare_data_from_FASTA

• get_one_hot_encoded_seqs

Functions for visualizations

• plot_arch_for_clusters

• plot_ggseqlogo_of_seqs

• viz_bas_vec

• viz_seqs_acgt_mat

• viz_pwm

Examples

# Here,we re-use the example input sequences and one-hot encoded matrix
# shipped with seqArchR. Please see examples in the corresponding man pages
# for generating a one-hot encoded input matrix from raw FASTA sequences
# in `prepare_data_from_FASTA`
#
inputSeqsMat <- readRDS(system.file("extdata", "tssSinuc.rds",
                             package = "seqArchR", mustWork = TRUE))

inputSeqsRaw <- readRDS(system.file("extdata", "tssSeqsRaw.rds",
                             package = "seqArchR", mustWork = TRUE))

# Set seqArchR configuration
seqArchRconfig <- seqArchR::set_config(
    parallelize = TRUE,
    n_cores = 2,
    n_runs = 100,
    k_min = 1,
    k_max = 20,
    mod_sel_type = "stability",
    bound = 10^-8,
    chunk_size = 100,
    flags = list(debug = FALSE, time = TRUE, verbose = TRUE,
        plot = FALSE)
)

# Run seqArchR
seqArchRresult <- seqArchR::seqArchR(config = seqArchRconfig,
                          seqs_ohe_mat = inputSeqsMat,
                          seqs_raw = inputSeqsRaw,
                          seqs_pos = seq(1,100,by=1),
                          total_itr = 2,
                          set_ocollation = c(TRUE, FALSE))

snikumbh/seqArchR documentation built on March 11, 2024, 7:06 p.m.