diff --git a/NEWS.md b/NEWS.md
index 845e561e..4e602024 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,6 @@
 # sigminer 2.3.1
 
+- Updated `sig_fit()` related documents for better usage (#454).
 - Added `cluster_col` to `show_group_enrichment()`.
 - Fixed the bug that error returned when `cluster_row = TRUE` & `return_list = TRUE` in function `show_group_enrichment()`.
 - Fixed the error in generating DBS and INDEL matrix when only one sample input (#453).
diff --git a/R/sig_fit.R b/R/sig_fit.R
index 736ca77a..90248835 100644
--- a/R/sig_fit.R
+++ b/R/sig_fit.R
@@ -49,6 +49,52 @@
 #'  Nature genetics 48.6 (2016): 600.
 #' @examples
 #' \donttest{
+#'
+#' # For mutational signatures ----------------
+#' # SBS is used for illustration, similar
+#' # operations can be applied to DBS, INDEL, CN, RS, etc.
+#'
+#' # Load simulated data
+#' data("simulated_catalogs")
+#' data = simulated_catalogs$set1
+#' data[1:5, 1:5]
+#'
+#' # Fitting with all COSMIC v2 reference signatures
+#' sig_fit(data, sig_index = "ALL")
+#' # Check ?sig_fit for sig_db options
+#' # e.g., use the COSMIC SBS v3
+#' sig_fit(data, sig_index = "ALL", sig_db = "SBS")
+#'
+#' # Fitting with specified signatures
+#' # opt 1. use selected reference signatures
+#' sig_fit(data, sig_index = c(1, 5, 9, 2, 13), sig_db = "SBS")
+#' # opt 2. use user specified signatures
+#' ref = get_sig_db()$db
+#' ref[1:5, 1:5]
+#' ref = ref[, 1:10]
+#' # The `sig` used here can be result object from `sig_extract`
+#' # or any reference matrix with similar structure (96-motif)
+#' v1 = sig_fit(data, sig = ref)
+#' v1
+#'
+#' # If possible, auto-reduce the reference signatures
+#' # for better fitting data from a sample
+#' v2 = sig_fit(data, sig = ref, auto_reduce = TRUE)
+#' v2
+#'
+#' all.equal(v1, v2)
+#'
+#' # Some samples reported signatures dropped
+#' # but its original activity values are 0s,
+#' # so the data remain same (0 -> 0)
+#' all.equal(v1[, 2], v2[, 2])
+#'
+#' # For COSMIC_10, 6.67638 -> 0
+#' v1[, 4]; v2[, 4]
+#' all.equal(v1[, 4], v2[, 4])
+#'
+#' # For general purpose -----------------------
+#'
 #' W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 #' colnames(W) <- c("sig1", "sig2")
 #' W <- apply(W, 2, function(x) x / sum(x))
diff --git a/R/sig_fit_bootstrap.R b/R/sig_fit_bootstrap.R
index f6a5bef6..117f5cc7 100644
--- a/R/sig_fit_bootstrap.R
+++ b/R/sig_fit_bootstrap.R
@@ -22,6 +22,12 @@
 #' @keywords bootstrap
 #' @seealso [report_bootstrap_p_value], [sig_fit], [sig_fit_bootstrap_batch]
 #' @examples
+#'
+#' # This function is designed for processing
+#' # one sample, thus is not very useful in practice
+#' # please check `sig_fit_bootstrap_batch`
+#'
+#' # For general purpose -------------------
 #' W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 #' colnames(W) <- c("sig1", "sig2")
 #' W <- apply(W, 2, function(x) x / sum(x))
diff --git a/R/sig_fit_bootstrap_batch.R b/R/sig_fit_bootstrap_batch.R
index fe28d1af..55c69d5b 100644
--- a/R/sig_fit_bootstrap_batch.R
+++ b/R/sig_fit_bootstrap_batch.R
@@ -23,6 +23,25 @@
 #' @seealso [sig_fit], [sig_fit_bootstrap]
 #'
 #' @examples
+#' # For mutational signatures ----------------
+#' # SBS is used for illustration, similar
+#' # operations can be applied to DBS, INDEL, CN, RS, etc.
+#'
+#' # Load simulated data
+#' data("simulated_catalogs")
+#' data = simulated_catalogs$set1
+#' data[1:5, 1:5]
+#'
+#' # Fitting with COSMIC reference signatures
+#' \donttest{
+#' # Generally set n = 100
+#' rv = sig_fit_bootstrap_batch(data,
+#'   sig_index = c(1, 5, 9, 2, 13),
+#'    sig_db = "SBS", n = 10)
+#' rv
+#' }
+#'
+#' # For general purpose --------------------
 #' W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 #' colnames(W) <- c("sig1", "sig2")
 #' W <- apply(W, 2, function(x) x / sum(x))
diff --git a/man/scoring.Rd b/man/scoring.Rd
index df3dc02d..04a0c623 100644
--- a/man/scoring.Rd
+++ b/man/scoring.Rd
@@ -4,7 +4,7 @@
 \alias{scoring}
 \title{Score Copy Number Profile}
 \usage{
-scoring(object, TD_size_cutoff = c(1000, 100000, 2000000), TD_cn_cutoff = Inf)
+scoring(object, TD_size_cutoff = c(1000, 1e+05, 2e+06), TD_cn_cutoff = Inf)
 }
 \arguments{
 \item{object}{a object of \link{CopyNumber}.}
diff --git a/man/sig_auto_extract.Rd b/man/sig_auto_extract.Rd
index 5e2a88e1..27b4097f 100644
--- a/man/sig_auto_extract.Rd
+++ b/man/sig_auto_extract.Rd
@@ -13,8 +13,8 @@ sig_auto_extract(
   ref_sigs = NULL,
   K0 = 25,
   nrun = 10,
-  niter = 200000,
-  tol = 0.0000001,
+  niter = 2e+05,
+  tol = 1e-07,
   cores = 1,
   optimize = FALSE,
   skip = FALSE,
diff --git a/man/sig_fit.Rd b/man/sig_fit.Rd
index 7a572453..df7c407a 100644
--- a/man/sig_fit.Rd
+++ b/man/sig_fit.Rd
@@ -113,6 +113,52 @@ feature CN is used.
 }
 \examples{
 \donttest{
+
+# For mutational signatures ----------------
+# SBS is used for illustration, similar
+# operations can be applied to DBS, INDEL, CN, RS, etc.
+
+# Load simulated data
+data("simulated_catalogs")
+data = simulated_catalogs$set1
+data[1:5, 1:5]
+
+# Fitting with all COSMIC v2 reference signatures
+sig_fit(data, sig_index = "ALL")
+# Check ?sig_fit for sig_db options
+# e.g., use the COSMIC SBS v3
+sig_fit(data, sig_index = "ALL", sig_db = "SBS")
+
+# Fitting with specified signatures
+# opt 1. use selected reference signatures
+sig_fit(data, sig_index = c(1, 5, 9, 2, 13), sig_db = "SBS")
+# opt 2. use user specified signatures
+ref = get_sig_db()$db
+ref[1:5, 1:5]
+ref = ref[, 1:10]
+# The `sig` used here can be result object from `sig_extract`
+# or any reference matrix with similar structure (96-motif)
+v1 = sig_fit(data, sig = ref)
+v1
+
+# If possible, auto-reduce the reference signatures
+# for better fitting data from a sample
+v2 = sig_fit(data, sig = ref, auto_reduce = TRUE)
+v2
+
+all.equal(v1, v2)
+
+# Some samples reported signatures dropped
+# but its original activity values are 0s,
+# so the data remain same (0 -> 0)
+all.equal(v1[, 2], v2[, 2])
+
+# For COSMIC_10, 6.67638 -> 0
+v1[, 4]; v2[, 4]
+all.equal(v1[, 4], v2[, 4])
+
+# For general purpose -----------------------
+
 W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 colnames(W) <- c("sig1", "sig2")
 W <- apply(W, 2, function(x) x / sum(x))
diff --git a/man/sig_fit_bootstrap.Rd b/man/sig_fit_bootstrap.Rd
index 38e4df49..390ca31a 100644
--- a/man/sig_fit_bootstrap.Rd
+++ b/man/sig_fit_bootstrap.Rd
@@ -102,6 +102,12 @@ This can be used to obtain the confidence of signature exposures or search
 the suboptimal decomposition solution.
 }
 \examples{
+
+# This function is designed for processing
+# one sample, thus is not very useful in practice
+# please check `sig_fit_bootstrap_batch`
+
+# For general purpose -------------------
 W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 colnames(W) <- c("sig1", "sig2")
 W <- apply(W, 2, function(x) x / sum(x))
diff --git a/man/sig_fit_bootstrap_batch.Rd b/man/sig_fit_bootstrap_batch.Rd
index 61c1fc7b..bf7f7905 100644
--- a/man/sig_fit_bootstrap_batch.Rd
+++ b/man/sig_fit_bootstrap_batch.Rd
@@ -52,6 +52,25 @@ a \code{list} of \code{data.table}.
 Read \link{sig_fit_bootstrap} for more option setting.
 }
 \examples{
+# For mutational signatures ----------------
+# SBS is used for illustration, similar
+# operations can be applied to DBS, INDEL, CN, RS, etc.
+
+# Load simulated data
+data("simulated_catalogs")
+data = simulated_catalogs$set1
+data[1:5, 1:5]
+
+# Fitting with COSMIC reference signatures
+\donttest{
+# Generally set n = 100
+rv = sig_fit_bootstrap_batch(data,
+  sig_index = c(1, 5, 9, 2, 13),
+   sig_db = "SBS", n = 10)
+rv
+}
+
+# For general purpose --------------------
 W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
 colnames(W) <- c("sig1", "sig2")
 W <- apply(W, 2, function(x) x / sum(x))
diff --git a/tests/testthat/test-roxytest-testexamples-sig_fit.R b/tests/testthat/test-roxytest-testexamples-sig_fit.R
index 8995d488..047de2fa 100644
--- a/tests/testthat/test-roxytest-testexamples-sig_fit.R
+++ b/tests/testthat/test-roxytest-testexamples-sig_fit.R
@@ -2,9 +2,55 @@
 
 # File R/sig_fit.R: @testexamples
 
-test_that("Function sig_fit() @ L99", {
+test_that("Function sig_fit() @ L145", {
   
   
+  
+  # For mutational signatures ----------------
+  # SBS is used for illustration, similar
+  # operations can be applied to DBS, INDEL, CN, RS, etc.
+  
+  # Load simulated data
+  data("simulated_catalogs")
+  data = simulated_catalogs$set1
+  data[1:5, 1:5]
+  
+  # Fitting with all COSMIC v2 reference signatures
+  sig_fit(data, sig_index = "ALL")
+  # Check ?sig_fit for sig_db options
+  # e.g., use the COSMIC SBS v3
+  sig_fit(data, sig_index = "ALL", sig_db = "SBS")
+  
+  # Fitting with specified signatures
+  # opt 1. use selected reference signatures
+  sig_fit(data, sig_index = c(1, 5, 9, 2, 13), sig_db = "SBS")
+  # opt 2. use user specified signatures
+  ref = get_sig_db()$db
+  ref[1:5, 1:5]
+  ref = ref[, 1:10]
+  # The `sig` used here can be result object from `sig_extract`
+  # or any reference matrix with similar structure (96-motif)
+  v1 = sig_fit(data, sig = ref)
+  v1
+  
+  # If possible, auto-reduce the reference signatures
+  # for better fitting data from a sample
+  v2 = sig_fit(data, sig = ref, auto_reduce = TRUE)
+  v2
+  
+  all.equal(v1, v2)
+  
+  # Some samples reported signatures dropped
+  # but its original activity values are 0s,
+  # so the data remain same (0 -> 0)
+  all.equal(v1[, 2], v2[, 2])
+  
+  # For COSMIC_10, 6.67638 -> 0
+  v1[, 4]; v2[, 4]
+  all.equal(v1[, 4], v2[, 4])
+  
+  # For general purpose -----------------------
+  
   W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
   colnames(W) <- c("sig1", "sig2")
   W <- apply(W, 2, function(x) x / sum(x))
diff --git a/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap.R b/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap.R
index cbf85b10..593de427 100644
--- a/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap.R
+++ b/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap.R
@@ -2,8 +2,14 @@
 
 # File R/sig_fit_bootstrap.R: @testexamples
 
-test_that("Function sig_fit_bootstrap() @ L61", {
+test_that("Function sig_fit_bootstrap() @ L67", {
   
+  
+  # This function is designed for processing
+  # one sample, thus is not very useful in practice
+  # please check `sig_fit_bootstrap_batch`
+  
+  # For general purpose -------------------
   W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
   colnames(W) <- c("sig1", "sig2")
   W <- apply(W, 2, function(x) x / sum(x))
diff --git a/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap_batch.R b/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap_batch.R
index 2a68f953..10f6a085 100644
--- a/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap_batch.R
+++ b/tests/testthat/test-roxytest-testexamples-sig_fit_bootstrap_batch.R
@@ -2,8 +2,27 @@
 
 # File R/sig_fit_bootstrap_batch.R: @testexamples
 
-test_that("Function sig_fit_bootstrap_batch() @ L44", {
+test_that("Function sig_fit_bootstrap_batch() @ L63", {
   
+  # For mutational signatures ----------------
+  # SBS is used for illustration, similar
+  # operations can be applied to DBS, INDEL, CN, RS, etc.
+  
+  # Load simulated data
+  data("simulated_catalogs")
+  data = simulated_catalogs$set1
+  data[1:5, 1:5]
+  
+  # Fitting with COSMIC reference signatures
+  
+  # Generally set n = 100
+  rv = sig_fit_bootstrap_batch(data,
+    sig_index = c(1, 5, 9, 2, 13),
+     sig_db = "SBS", n = 10)
+  rv
+  
+  
+  # For general purpose --------------------
   W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
   colnames(W) <- c("sig1", "sig2")
   W <- apply(W, 2, function(x) x / sum(x))