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Editor to share with you the example analysis of PWM matrix in motif. I hope you will get something after reading this article. Let's discuss it together.

The situation of a motif can be expressed intuitively by consistent sequences and sequence logo, but when predicting the binding sites of motif, it is impossible to accurately judge the existence of the corresponding motif on the query sequence only according to these information. The analysis that predicts whether there is a specific motif site on the input sequence, called motif scanning, is illustrated as follows

Is to find the location of a particular motif on the input sequence. In order to meet the requirements of motif scanning analysis, for motif, we must provide an effective information that can represent motif and can be used for sequence lookup. Based on this starting point, the concept of PWM matrix is proposed.

PWM matrix has different names in different articles. The following three matrices are actually PWM matrices.

Position weight matrix (PWM)

Position-specific weight matirx (PSWM)

Position-specific scoring matrix (PSSM)

The PWM matrix is developed from the PFM matrix. The PFM matrix shown in the following figure is an example.

According to the base frequency distribution matrix, the base frequency distribution matrix is first calculated, which is called position probability matrixa, abbreviated as PPM matrix, as follows

In the PPM matrix, the frequency of bases is used as probability, and different positions can be seen as an independent event. According to the PPM matrix, the probability of a motif sequence can be calculated. According to the above PPM matrix, the probability of GAGGTAAAC occurrence is

Based on the PPM matrix, the corresponding value is corrected by the base distribution frequency of the background sequence, and the PWM matrix can be obtained. The formula is as follows.

It is to divide the corresponding value in the PPM matrix in addition to the frequency of the corresponding base in the background sequence, and then take the log2 logarithm value. In most cases, we think that the contents of the four bases are equal in the genome, so the background frequency of each base is 0.25. Taking the 0.3 of the first row of the PPM matrix as an example, we first divide 0.3 by the frequency of A base in the background sequence, and then take the log2 logarithm, the final value is 0.26.

In this way, the PWM matrix is constructed as follows

It should be noted that the probability of bases in the background sequence is not all 0.25. in some species with high or low GC content, the distribution frequencies of the four bases are not equal, so it is necessary to determine the base frequency in the background sequence according to the real base distribution.

According to the PWM matrix, the sequence can be scored and the final score can be used to determine whether it is a potential motif. According to the above PWM matrix, the score of GAGGTAAAC is

Score > = 0, indicating that this sequence is a potential functional site, score < 0, indicating that it is a random sequence. According to the PWM matrix, we can effectively judge whether there are real motif sites in the input sequence.

After reading this article, I believe you have some understanding of "sample Analysis of PWM Matrix in motif". If you want to know more about it, you are welcome to follow the industry information channel. Thank you for reading!

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