Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.align = "center",
out.width = "100%",
fig.width = 9, fig.height = 7
)
## -----------------------------------------------------------------------------
set.seed(42)
library(NAIR)
dir_out <- tempdir()
toy_data <- simulateToyData()
head(toy_data)
## -----------------------------------------------------------------------------
nrow(toy_data)
## ----eval = FALSE-------------------------------------------------------------
# library(magrittr) # For pipe operator (%>%)
# toy_data %>%
# filterInputData("CloneSeq", drop_matches = "\\W") %>%
# buildNet("CloneSeq") %>%
# addNodeStats("all") %>%
# addClusterMembership("greedy", cluster_id_name = "cluster_greedy") %>%
# addClusterMembership("leiden", cluster_id_name = "cluster_leiden") %>%
# addClusterStats("cluster_leiden", "CloneSeq", "CloneCount") %>%
# addPlots(color_nodes_by = c("cluster_leiden", "cluster_greedy"),
# color_scheme = "Viridis"
# ) %>%
# labelClusters("cluster_leiden", cluster_id_col = "cluster_leiden") %>%
# labelClusters("cluster_greedy", cluster_id_col = "cluster_greedy") %>%
# saveNetwork(output_dir = tempdir(), output_name = "my_network")
## -----------------------------------------------------------------------------
net <- buildRepSeqNetwork(toy_data, "CloneSeq")
net <- addPlots(net, color_nodes_by = "SampleID")
## ----eval = FALSE-------------------------------------------------------------
# net <- addNodeStats(net, stats_to_include = "all")
## ----eval = FALSE-------------------------------------------------------------
# net <- addClusterStats(net, cluster_fun = "walktrap",
# cluster_id_name = "cluster_walktrap")
## -----------------------------------------------------------------------------
net <- addClusterMembership(net,
cluster_fun = "leiden",
cluster_id_name = "cluster_leiden"
)
net <- addClusterMembership(net,
cluster_fun = "louvain",
cluster_id_name = "cluster_louvain"
)
## -----------------------------------------------------------------------------
net <- addPlots(net,
color_nodes_by = "cluster_louvain",
color_scheme = "Viridis"
)
net <- labelClusters(net,
cluster_id_col = "cluster_louvain",
top_n_clusters = 7,
size = 7
)
net$plots$cluster_louvain
## -----------------------------------------------------------------------------
set.seed(42)
small_sample <- simulateToyData(1, sample_size = 10, prefix_length = 1)
net <- buildNet(small_sample, "CloneSeq", plot_title = NULL)
net <- labelNodes(net, "CloneSeq", size = 4)
net$plots[[1]]
## ----eval = FALSE-------------------------------------------------------------
# saveNetwork(net, output_dir = dir_out, output_type = "individual")
## ----eval = FALSE-------------------------------------------------------------
# saveNetworkPlots(net$plots, outfile = file.path(dir_out, "plots.pdf"))
## ----eval = FALSE-------------------------------------------------------------
# dat <- loadDataFromFileList(list.files(my_dir), input_type = "rds")
## ----eval = FALSE-------------------------------------------------------------
# loadDataFromFileList(list.files(my_dir),
# input_type = "table",
# read.args = list(
# header = TRUE,
# sep = " ",
# dec = ",",
# na.strings = "NA!",
# row.names = 1,
# col.names = c("RowID",
# "CloneSeq", "CloneFrequency",
# "CloneCount", "VGene"
# )
# )
# )
## ----eval = FALSE-------------------------------------------------------------
# save(df_sample1, file = file_1)
# save(df_sample2, file = file_2)
# save(df_sample3, file = file_3)
# loadDataFromFileList(c(file_1, file_2, file_3),
# input_type = "rda",
# data_symbols = c("df_sample1",
# "df_sample2",
# "df_sample3"
# )
# )
## ----eval = FALSE-------------------------------------------------------------
# dat <- combineSamples(list.files(my_dir),
# input_type = "rds",
# min_seq_length = 7,
# drop_matches = "[*|_]",
# subset_cols = c("CloneSeq", "CloneCount", "VGene"),
# sample_ids = 1:5,
# subject_ids = c(1, 2, 2, 3, 3),
# group_ids = c(1, 1, 1, 2, 2)
# )
## -----------------------------------------------------------------------------
filtered_data <- filterInputData(toy_data,
seq_col = "CloneSeq",
min_seq_length = 13,
drop_matches = "GGGG",
subset_cols = c("CloneFrequency", "SampleID"),
count_col = "CloneCount",
verbose = TRUE
)
## ----eval = FALSE-------------------------------------------------------------
# my_data <- data.frame(
# clone_seq = c("ATCG", rep("ACAC", 2), rep("GGGG", 4)),
# clone_count = rep(1, 7),
# clone_freq = rep(1/7, 7),
# time_point = c("t_0", rep(c("t_0", "t_1"), 3)),
# subject_id = c(rep(1, 5), rep(2, 2))
# )
#
# # group clones by time point and subject ID
# data_agg_time_subject <-
# aggregateIdenticalClones(my_data,
# clone_col = "clone_seq",
# count_col = "clone_count",
# freq_col = "clone_freq",
# grouping_cols = c("subject_id", "time_point")
# )
## ----eval = FALSE-------------------------------------------------------------
# nbd <- getNeighborhood(toy_data,
# seq_col = "CloneSeq",
# target_seq = "GGGGGGGAATTGG"
# )
## ----eval = FALSE-------------------------------------------------------------
# net <- generateNetworkObjects(toy_data, "CloneSeq")
## ----eval = FALSE-------------------------------------------------------------
# net$igraph <- generateNetworkGraph(net$adjacency_matrix)
## ----eval = FALSE-------------------------------------------------------------
# output$adjacency_matrix <- generateAdjacencyMatrix(toy_data$CloneSeq)
#
# # use same settings from original call to buildRepSeqNetwork()
# net$adjacency_matrix <- generateAdjacencyMatrix(
# net$node_data$CloneSeq,
# dist_type = net$details$dist_type,
# dist_cutoff = net$details$dist_cutoff,
# drop_isolated_nodes = net$details$drop_isolated_nodes
# )
## ----include=FALSE, eval = FALSE----------------------------------------------
# # clean up temp directory
# file.remove(
# file.path(
# tempdir(),
# c("MyRepSeqNetwork_NodeMetadata.csv",
# "MyRepSeqNetwork_ClusterMetadata.csv",
# "MyRepSeqNetwork.pdf",
# "MyRepSeqNetwork_EdgeList.txt",
# "MyRepSeqNetwork_AdjacencyMatrix.mtx",
# "MyRepSeqNetwork_Details.rds",
# "MyRepSeqNetwork_Plots.rds",
# "MyRepSeqNetwork_GraphLayout.txt",
# "MyRepSeqNetwork.rds"
# )
# )
# )
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