Supplementary Materials
Supplementary Tables
Supplementary Table S1. ChIP-Seq Datasets [1]
Dataset
DM230
Mark
PolII (RNA polymerase II)
Species/Tissue
Mouse/Liver
GEO Accession
GSM722763
DM05
p300 (co-activator protein)
Mouse/Liver
GSM722762
DM721
H3K27ac (H3 lysine 27 acetylation)
Mouse/Liver
GSM851275
Supplementary Table S2. Motif Datasets [1]
Case
Motif Dataset
Motif Input Format
Study
1
2
3
Number of
ChIP-Seq
Motifs
Dataset
DREME_DM230
MEME’s output
1 DM230
MEME_DM230
MEME’s output
20 DM230
PScanChIP_DM230
Jaspar
14 DM230
RSAT_peak-motifs_DM230
TRANSFAC-like
10 DM230
W-ChIPMotifs_DM230
PSSM
11 DM230
MEME_DM05
MEME’s output
46 DM05
MEME-ChIP_DM05
MEME’s output
4 DM05
PScanChIP_DM05
Jaspar
16 DM05
RSAT_peak-motifs_DM05
TRANSFAC-like
17 DM05
W-ChIPMotifs_DM05
PSSM
11 DM05
DREME_DM721
MEME’s output
16 DM721
MEME-ChIP_DM721
MEME’s output
11 DM721
PScanChIP_DM721
Jaspar
37 DM721
RSAT_peak-motifs_DM721
TRANSFAC-like
40 DM721
1
Supplementary Figures
Supplementary Figure S1: An illustration of a motif in a position specific probability matrix used
by MOTIFSIM. The four columns represent A, C, G, and T nucleotides respectively. The length of this
motif is seven, which is the number of rows in the matrix. Each element in the matrix is a probability
value of a nucleotide.
Supplementary Figure S2: Network architecture of MOTIFSIM web tool. The HAProxy load balancer
directs web traffic to different Apache web server nodes on the cluster.
2
Conversion of different motif input formats to position specific probability
matrices
The procedures for converting different motif input formats, which are described in the user manuals, to
position specific probability matrices [2] used by MOTIFSIM are slightly different because of their
different structures. An illustration of a position specific probability matrix used by MOTIFSIM is in
Figure S1.
1. TRANFAC, TRANFAC-like, Position Specific Scoring Matrix (PSSM), and vertical matrix
formats to position specific probability matrices
We applied the same conversion procedure for these motif input formats because they have four
columns for A, C, G, and T nucleotides. The sum of four values for A, C, G, and T in each row for
each input format must be identical. To convert the input matrix (green matrix below) to a position
specific probability matrix (yellow matrix below), each element in a position specific probability
matrix is calculated by taking the value of each element in the input matrix divided by the sum of the
four values in each row in the input matrix. The sum of the four values for A, C, G, and T in each row
of a position specific probability matrix must be 1.
A
73
44
485
0
79
0
C
81
578
65
570
0
0
G
407
0
0
52
0
622
T
61
0
72
0
543
0
Sum
622
622
622
622
622
622
A
0.1174
0.0707
0.7797
0.0000
0.1270
0.0000
C
0.1302
0.9293
0.1045
0.9164
0.0000
0.0000
G
0.6543
0.0000
0.0000
0.0836
0.0000
1.0000
T
0.0981
0.0000
0.1158
0.0000
0.8730
0.0000
2. Jaspar and horizontal matrix formats to position specific probability matrices
3
Sum
1
1
1
1
1
1
The Jaspar and horizontal matrix formats have four rows represent A, C, G, and T nucleotides
respectively. The sum of four values in each column must be identical. To convert the input matrix
(blue matrix below) to a position specific probability matrix (yellow matrix below), we divide the
value of each element in each column of the input matrix by the sum of four values in that same
column. The results of the entire column are transposed to make the entire row for the position
specific probability matrix.
A
C
G
T
[
[
[
[
Sum
8
1
3
2
13
0
1
0
0
0
13
1
3
0
11
0
2
2
0
10
0
13
0
1
14
0
0
0
3
8
2
1
14
14
14
14
14
14
14
14
]
]
]
]
A
0.5714
0.9286
0.0000
0.2143
C
0.0714
0.0000
0.0000
0.0000
G
0.2143
0.0714
0.9286
0.7857
T Sum
0.1429
1
0.0000
1
0.0714
1
0.0000
1
0.1429
0.0000
1.0000
0.2143
0.1429
0.9286
0.0000
0.5714
0.0000
0.0000
0.0000
0.1429
0.7143
0.0714
0.0000
0.0714
1
1
1
1
3. Consensus sequence format to position specific probability matrices
Each letter in a consensus sequence is converted to one row of a position specific probability matrix
using the IUPAC nucleotide code [3] in the table below.
IUPAC Nucleotide Code
Base
A
C
G
T (or U)
R
Y
S
W
K
M
B
D
Adenine
Cytosine
Guanine
Thymine (or Uracil)
A or G
C or T
G or C
A or T
G or T
A or C
C or G or T
A or G or T
Corresponding Row in Position Specific
Probability Matrix
1.0000 0.0000 0.0000
0.0000
0.0000 1.0000 0.0000
0.0000
0.0000 0.0000 1.0000
0.0000
0.0000 0.0000 0.0000
1.0000
0.5000 0.0000 0.5000
0.0000
0.0000 0.5000 0.0000
0.5000
0.0000 0.5000 0.5000
0.0000
0.5000 0.0000 0.0000
0.5000
0.0000 0.0000 0.5000
0.5000
0.5000 0.5000 0.0000 0.0000
0.0000 0.3333 0.3333
0.3333
0.3333 0.0000 0.3333 0.3333
4
H
V
A or C or T
A or C or G
N
any base
0.3333
0.3333
0.2500
0.3333
0.3333
0.2500
0.0000
0.3333
0.2500
0.3333
0.0000
0.2500
4. Sequence alignment format to position specific probability matrix
First, the sequence alignment is converted to a profile matrix, which has four rows representing A, C,
G, and T nucleotides. Then, the profile matrix is converted to a position specific probability matrix.
An example of this conversion is below.
A
C
G
T
Sum
AACACGTGGC
A
3
3
2
4
0
0
0
0
0
1
0.6000
0.2000
0.2000
0.0000
1
GCCACGTGCC
C
1
1
3
1
4
1
0
0
2
2
0.6000
0.2000
0.2000
0.0000
1
CGCATGTGCA
G
1
1
0
0
0
4
0
4
1
1
0.4000
0.6000
0.0000
0.0000
1
AAAACGTGTT
T
0
0
0
0
1
0
5
1
2
1
0.8000
0.2000
0.0000
0.0000
1
AAACCCTTTG
Sum
5
5
5
5
5
5
5
5
5
5
0.0000
0.8000
0.0000
0.2000
1
0.0000
0.2000
0.8000
0.0000
1
0.0000
0.0000
0.0000
1.0000
1
0.0000
0.0000
0.8000
0.2000
1
0.0000
0.4000
0.2000
0.4000
1
0.2000
0.4000
0.2000
0.2000
1
Sequence Alignment
Profile Matrix
Position Specific Probability
Matrix
Calculate the absolute value of the difference between each pair of
corresponding matrix elements
The difference between two corresponding matrix elements
p i j ,k
and
p i 1 j , k
in the overlapping window
p
p
between two matrices pi and pi 1 is calculated by subtracting element i j , k from element i 1 j , k . The
difference can be positive or negative. Therefore, the absolute value of the difference is calculated. The
example below illustrates this process. The bold rectangle is the overlapping window. The difference
5
between the first element (red) in matrix pi (yellow) and the first element (red) in matrix pi 1 (green)
is calculated in the first element (red) of the deference matrix d i , i 1 (purple).
References
1. Tran, N.T.L. and C-H. Huang. 2014. A survey of motif finding Web tools for detecting binding
site motifs in ChIP-Seq data. Biology Direct 9:1-22.
2. Li, H. 2002. Computational approaches to identifying transcription factor binding sites in yeast
genome. Methods in Enzymology: Guides to Yeast Genetics and Molecular Biology, Part B
350:484-495.
3. IUPAC nucleotide code. Available at http://www.bioinformatics.org/sms/iupac.html.
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