diff --git a/base/exports.jl b/base/exports.jl
index ea14ae36e8d98..5b153f7b3ae9b 100644
--- a/base/exports.jl
+++ b/base/exports.jl
@@ -632,6 +632,7 @@ export
     cond,
     condskeel,
     cross,
+    ctranspose!,
     ctranspose,
     det,
     diag,
@@ -692,6 +693,7 @@ export
     svdvals,
     sylvester,
     trace,
+    transpose!,
     transpose,
     tril!,
     tril,
diff --git a/base/sparse.jl b/base/sparse.jl
index 87c381af430aa..3e144fa60aa1b 100644
--- a/base/sparse.jl
+++ b/base/sparse.jl
@@ -4,6 +4,7 @@ module SparseMatrix
 
 importall Base
 import Base.NonTupleType, Base.float, Base.Order, Base.Sort.Forward
+import Base.transpose!, Base.ctranspose!
 
 export SparseMatrixCSC,
        blkdiag, dense, diag, diagm, droptol!, dropzeros!, etree, full,
diff --git a/base/sparse/csparse.jl b/base/sparse/csparse.jl
index 16cc05526d9cc..2cd1816f461a7 100644
--- a/base/sparse/csparse.jl
+++ b/base/sparse/csparse.jl
@@ -123,7 +123,7 @@ end
 # Based on Direct Methods for Sparse Linear Systems, T. A. Davis, SIAM, Philadelphia, Sept. 2006.
 # Section 2.5: Transpose
 # http://www.cise.ufl.edu/research/sparse/CSparse/
-function transpose!{Tv,Ti}(S::SparseMatrixCSC{Tv,Ti}, T::SparseMatrixCSC{Tv,Ti})
+function transpose!{Tv,Ti}(T::SparseMatrixCSC{Tv,Ti}, S::SparseMatrixCSC{Tv,Ti})
     (mS, nS) = size(S)
     nnzS = nnz(S)
     colptr_S = S.colptr
@@ -162,10 +162,10 @@ function transpose{Tv,Ti}(S::SparseMatrixCSC{Tv,Ti})
     nzval_T = Array(Tv, nnzS)
 
     T = SparseMatrixCSC(mT, nT, colptr_T, rowval_T, nzval_T)
-    return transpose!(S, T)
+    return transpose!(T, S)
 end
 
-function ctranspose!{Tv,Ti}(S::SparseMatrixCSC{Tv,Ti}, T::SparseMatrixCSC{Tv,Ti})
+function ctranspose!{Tv,Ti}(T::SparseMatrixCSC{Tv,Ti}, S::SparseMatrixCSC{Tv,Ti})
     (mS, nS) = size(S)
     nnzS = nnz(S)
     colptr_S = S.colptr
@@ -204,7 +204,7 @@ function ctranspose{Tv,Ti}(S::SparseMatrixCSC{Tv,Ti})
     nzval_T = Array(Tv, nnzS)
 
     T = SparseMatrixCSC(mT, nT, colptr_T, rowval_T, nzval_T)
-    return ctranspose!(S, T)
+    return ctranspose!(T, S)
 end
 
 # Compute the elimination tree of A using triu(A) returning the parent vector.
diff --git a/base/sparse/sparsematrix.jl b/base/sparse/sparsematrix.jl
index c0fadc45b39e6..0613faf9345fb 100644
--- a/base/sparse/sparsematrix.jl
+++ b/base/sparse/sparsematrix.jl
@@ -2067,8 +2067,8 @@ function sortSparseMatrixCSC!{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}; sortindices::Sym
     if sortindices == :doubletranspose
         nB, mB = size(A)
         B = SparseMatrixCSC(mB, nB, Array(Ti, nB+1), similar(A.rowval), similar(A.nzval))
-        transpose!(A, B)
         transpose!(B, A)
+        transpose!(A, B)
         return A
     end
 
diff --git a/doc/stdlib/base.rst b/doc/stdlib/base.rst
index 210dd3c5fa1e9..b0cf467def808 100644
--- a/doc/stdlib/base.rst
+++ b/doc/stdlib/base.rst
@@ -4313,6 +4313,10 @@ Indexing, Assignment, and Concatenation
 
    Like :func:`permutedims`, except the inverse of the given permutation is applied.
 
+.. function:: permutedims!(dest,src,perm)
+
+   Permute the dimensions of array ``src`` and store the result in the array ``dest``. ``perm`` is a vector specifying a permutation of length ``ndims(src)``. The preallocated array ``dest`` should have ``size(dest)=size(src)[perm]`` and is completely overwritten. No in-place permutation is supported and unexpected results will happen if `src` and `dest` have overlapping memory regions.
+
 .. function:: squeeze(A, dims)
 
    Remove the dimensions specified by ``dims`` from array ``A``
diff --git a/doc/stdlib/linalg.rst b/doc/stdlib/linalg.rst
index 1b39832b90056..5bec267b1f210 100644
--- a/doc/stdlib/linalg.rst
+++ b/doc/stdlib/linalg.rst
@@ -552,10 +552,18 @@ Linear algebra functions in Julia are largely implemented by calling functions f
 
    The transposition operator (``.'``).
 
+.. function:: transpose!(dest,src)
+
+   Transpose array ``src`` and store the result in the preallocated array ``dest``, which should have a size corresponding to ``(size(src,2),size(src,1))``. No in-place transposition is supported and unexpected results will happen if `src` and `dest` have overlapping memory regions.
+
 .. function:: ctranspose(A)
 
    The conjugate transposition operator (``'``).
 
+.. function:: ctranspose!(dest,src)
+
+   Conjugate transpose array ``src`` and store the result in the preallocated array ``dest``, which should have a size corresponding to ``(size(src,2),size(src,1))``. No in-place transposition is supported and unexpected results will happen if `src` and `dest` have overlapping memory regions.
+
 .. function:: eigs(A, [B,]; nev=6, which="LM", tol=0.0, maxiter=1000, sigma=nothing, ritzvec=true, v0=zeros((0,))) -> (d,[v,],nconv,niter,nmult,resid)
 
    ``eigs`` computes eigenvalues ``d`` of ``A`` using Lanczos or Arnoldi iterations for real symmetric or general nonsymmetric matrices respectively. If ``B`` is provided, the generalized eigen-problem is solved.  The following keyword arguments are supported: