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214 changes: 196 additions & 18 deletions BINF2025_TP3.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,7 @@
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyNSXnqaXAUgZK9rmJ1TWbGo"
"provenance": []
},
"kernelspec": {
"name": "python3",
Expand Down Expand Up @@ -70,11 +69,38 @@
"id": "qqiiq5bcxYvM"
}
},
{
"cell_type": "code",
"source": [
"+ 1+1+1.5+1-1-1-1-1+1+1+1.5+2+1+1+1"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "R--yDLlLtG4n",
"outputId": "e30f9f6c-a0c9-43e5-b8f0-1931c38946db"
},
"execution_count": 1,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"9.0"
]
},
"metadata": {},
"execution_count": 1
}
]
},
{
"cell_type": "markdown",
"source": [
"```markdown\n",
"Votre réponse ici\n",
"On trouve 9\n",
"\n",
"```"
],
"metadata": {
Expand All @@ -94,7 +120,10 @@
"cell_type": "markdown",
"source": [
"```markdown\n",
"Votre réponse ici\n",
"Le meilleur alignement est\n",
"A-TG\n",
"ACTG\n",
"avec une distance de 1\n",
"```"
],
"metadata": {
Expand Down Expand Up @@ -125,7 +154,9 @@
"cell_type": "markdown",
"source": [
"```markdown\n",
"Votre réponse ici\n",
"Score de 0.5 avec\n",
"x = -T-AT\n",
"y = ATGAC\n",
"```"
],
"metadata": {
Expand Down Expand Up @@ -177,12 +208,24 @@
{
"cell_type": "code",
"source": [
"#Votre code ici"
"def levenshtein(x,y):\n",
" if len(x)==0:\n",
" return len(y)\n",
" elif len(y)==0:\n",
" return len(x)\n",
" else:\n",
" if x[0]==y[0]:\n",
" return levenshtein(x[1:],y[1:])\n",
" else:\n",
" min1 = levenshtein(x[1:],y)\n",
" min2 = levenshtein(x,y[1:])\n",
" min3 = levenshtein(x[1:],y[1:])\n",
" return min(min1,min2,min3)+1"
],
"metadata": {
"id": "FJR69IEQ4aHv"
},
"execution_count": null,
"execution_count": 14,
"outputs": []
},
{
Expand All @@ -201,6 +244,33 @@
"id": "arFVwA6E5NWn"
}
},
{
"cell_type": "code",
"source": [
"print(levenshtein('CCAG','CA'))\n",
"print(levenshtein('CCGT','CGTCA'))\n",
"print(levenshtein('AY678264*','OQ870305*'))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TL30OBd45cDV",
"outputId": "248ae1c6-9a48-4328-aba0-273d27e66aad"
},
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2\n",
"3\n",
"7\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
Expand All @@ -226,12 +296,45 @@
{
"cell_type": "code",
"source": [
"#Votre code ici"
"import numpy as np\n",
"\n",
"def gap_penality(go, ge, n):\n",
" return -(go + ge * n)\n",
"import numpy as np\n",
"\n",
"def sw_fwd(x: str, y: str, cmap: dict, sigma: np.ndarray, goge: list) -> (np.ndarray, np.ndarray):\n",
" # Initialisation des matrices S et B\n",
" go, ge = goge\n",
" S = np.zeros((len(x) + 1, len(y) + 1))\n",
" B = np.zeros((len(x) + 1, len(y) + 1), dtype=int)\n",
"\n",
" # Remplissage des matrices\n",
" for i in range(1, len(x) + 1):\n",
" for j in range(1, len(y) + 1):\n",
" # Calcul des scores pour les différentes opérations\n",
" match = S[i-1, j-1] + sigma[cmap[x[i-1]], cmap[y[j-1]]]\n",
" delete = max([S[i-k, j] - (go + ge * k) for k in range(1, i+1)])\n",
" insert = max([S[i, j-k] - (go + ge * k) for k in range(1, j+1)])\n",
"\n",
" # Calcul du score maximal\n",
" S[i, j] = max(0, match, delete, insert)\n",
"\n",
" # Mise à jour de la matrice B\n",
" if S[i, j] == 0:\n",
" B[i, j] = 0\n",
" elif S[i, j] == match:\n",
" B[i, j] = 1\n",
" elif S[i, j] == delete:\n",
" B[i, j] = 2\n",
" else:\n",
" B[i, j] = 3\n",
"\n",
" return S, B"
],
"metadata": {
"id": "njn3JB0b-WHj"
"id": "g08UKhBu8FRT"
},
"execution_count": null,
"execution_count": 50,
"outputs": []
},
{
Expand All @@ -250,12 +353,37 @@
{
"cell_type": "code",
"source": [
"#Votre code ici"
"import numpy as np\n",
"\n",
"def sw_bwd(x, y, S, B):\n",
" n = len(x)\n",
" m = len(y)\n",
" align_x = \"\"\n",
" align_y = \"\"\n",
" i, j = np.unravel_index(S.argmax(), S.shape)\n",
" score = S[i, j]\n",
"\n",
" while B[i, j] != 0 and i > 0 and j > 0: # Added conditions to prevent index error\n",
" if B[i, j] == 1:\n",
" align_x = x[i - 1] + align_x\n",
" align_y = y[j - 1] + align_y\n",
" i -= 1\n",
" j -= 1\n",
" elif B[i, j] == 2:\n",
" align_x = x[i - 1] + align_x\n",
" align_y = \"-\" + align_y\n",
" i -= 1\n",
" elif B[i, j] == 3:\n",
" align_x = \"-\" + align_x\n",
" align_y = y[j - 1] + align_y\n",
" j -= 1\n",
"\n",
" return align_x, align_y, score"
],
"metadata": {
"id": "ij9JDpBm_UZ7"
},
"execution_count": null,
"execution_count": 51,
"outputs": []
},
{
Expand All @@ -281,9 +409,48 @@
"metadata": {
"id": "JUtYRFTBAwwZ"
},
"execution_count": null,
"execution_count": 52,
"outputs": []
},
{
"cell_type": "code",
"source": [
"S, B = sw_fwd('TCGC', 'CTTAG', cmap, m, (go, ge))\n",
"print(S)\n",
"sw_bwd('TCGC', 'CTTAG', S, B)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mhjC0JP-9Pyz",
"outputId": "50cd3311-f13c-48d4-b931-c403636c4c44"
},
"execution_count": 53,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[0. 0. 0. 0. 0. 0. ]\n",
" [0. 0. 1. 1. 0.5 0. ]\n",
" [0. 1. 0.5 0.5 0.5 0. ]\n",
" [0. 0.5 0.5 0. 0. 1.5]\n",
" [0. 1. 0.5 0. 0. 1. ]]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"('TCG', 'TAG', 1.5)"
]
},
"metadata": {},
"execution_count": 53
}
]
},
{
"cell_type": "markdown",
"source": [
Expand All @@ -293,6 +460,17 @@
"id": "eMGh4K5aIFxE"
}
},
{
"cell_type": "code",
"source": [
"from IPython.display import HTML"
],
"metadata": {
"id": "7vtyQxHW9GSG"
},
"execution_count": 21,
"outputs": []
},
{
"cell_type": "code",
"source": [
Expand All @@ -301,12 +479,12 @@
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 60
"height": 61
},
"id": "joHNwJ9AIf6F",
"outputId": "a9206810-a083-4d86-8b14-38183f1dd80c"
"outputId": "4c50d6ce-c8f5-4866-b4bb-aaf7167cdd14"
},
"execution_count": null,
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
Expand All @@ -319,7 +497,7 @@
]
},
"metadata": {},
"execution_count": 18
"execution_count": 22
}
]
},
Expand Down Expand Up @@ -387,7 +565,7 @@
"cell_type": "markdown",
"source": [
"```markdown\n",
"Votre réponse ici\n",
"le score moyen attendu pour une superposition sans trou de deux séquences aléatoires de taille N est N/4\n",
"```"
],
"metadata": {
Expand Down