diff --git a/alphadia/libtransform.py b/alphadia/libtransform.py index 805b4073..a77c6643 100644 --- a/alphadia/libtransform.py +++ b/alphadia/libtransform.py @@ -320,7 +320,7 @@ def forward(self, input: SpecLibBase) -> SpecLibBase: device = utils.get_torch_device(self.use_gpu) - model_mgr = ModelManager(device=device) + model_mgr = ModelManager(device=device, charged_frag_types=charged_frag_types) # will load other model than default generic if self.peptdeep_model_type: diff --git a/alphadia/outputtransform.py b/alphadia/outputtransform.py index d98ad9cd..85ce4d2a 100644 --- a/alphadia/outputtransform.py +++ b/alphadia/outputtransform.py @@ -421,6 +421,8 @@ def build_transfer_model(self, save=True): max_lr=self.config["transfer_learning"]["max_lr"], nce=self.config["transfer_learning"]["nce"], instrument=self.config["transfer_learning"]["instrument"], + fragment_types=self.config["transfer_library"]["fragment_types"], + max_charge=self.config["transfer_library"]["max_charge"], ) rt_stats = tune_mgr.finetune_rt(transfer_lib.precursor_df) charge_stats = tune_mgr.finetune_charge(transfer_lib.precursor_df) diff --git a/alphadia/transferlearning/train.py b/alphadia/transferlearning/train.py index b26e7899..3c083c0a 100644 --- a/alphadia/transferlearning/train.py +++ b/alphadia/transferlearning/train.py @@ -3,7 +3,7 @@ import numpy as np import pandas as pd import torch -from alphabase.peptide.fragment import remove_unused_fragments +from alphabase.peptide.fragment import get_charged_frag_types, remove_unused_fragments from alphabase.peptide.mobility import ccs_to_mobility_for_df, mobility_to_ccs_for_df from alphabase.peptide.precursor import refine_precursor_df from peptdeep.model.charge import ChargeModelForModAASeq @@ -218,8 +218,9 @@ def __init__( max_lr: float = 0.0005, nce: float = 25, instrument: str = "Lumos", + fragment_types: list[str] | None = None, + max_charge: int | None = None, ): - super().__init__(mask_modloss, device) self._test_interval = test_interval self._train_fraction = train_fraction self._validation_fraction = validation_fraction @@ -233,11 +234,16 @@ def __init__( self.device = device self.early_stopping = EarlyStopping(patience=(lr_patience // test_interval) * 4) - + self.charged_frag_types = ( + get_charged_frag_types(fragment_types, max_charge) + if fragment_types + else None + ) assert ( self._train_fraction + self._validation_fraction + self._test_fraction <= 1.0 ), "The sum of the train, validation and test fractions should be less than or equal to 1.0" + super().__init__(mask_modloss, device, self.charged_frag_types) def _reset_frag_idx(self, df): """ diff --git a/nbs/tutorial_nbs/additional_frags.ipynb b/nbs/tutorial_nbs/additional_frags.ipynb new file mode 100644 index 00000000..0a80e8d4 --- /dev/null +++ b/nbs/tutorial_nbs/additional_frags.ipynb @@ -0,0 +1,480 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from alphabase.spectral_library.base import SpecLibBase\n", + "from alphabase.spectral_library.flat import SpecLibFlat\n", + "from alphadia.workflow.reporting import *\n", + "from alphadia.transferlearning.train import *\n", + "\n", + "import seaborn as sns\n", + "sns.set()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "transfer_lib = SpecLibFlat()\n", + "transfer_lib.load_hdf('alphaDia/2oh_evidence_txt_0_batch_0.hdf', load_mod_seq=True)\n", + "if \"precursor_idx\" not in transfer_lib.precursor_df.columns:\n", + " transfer_lib.precursor_df[\"precursor_idx\"] = transfer_lib.precursor_df.index" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Finetuning starting from a default model and training for more fragment types " + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:48:36> The loaded weights are not strictly matched with the current model, some layers are still randomly initialized. Make sure to train the model or load different weights before prediction. The following keys had size mismatches: ['output_nn.nn.2.weight', 'output_nn.nn.2.bias'] The following keys were unexpected: ['modloss_nn.0.bert.layer.0.attention.self.query.weight', 'modloss_nn.0.bert.layer.0.attention.self.query.bias', 'modloss_nn.0.bert.layer.0.attention.self.key.weight', 'modloss_nn.0.bert.layer.0.attention.self.key.bias', 'modloss_nn.0.bert.layer.0.attention.self.value.weight', 'modloss_nn.0.bert.layer.0.attention.self.value.bias', 'modloss_nn.0.bert.layer.0.attention.output.dense.weight', 'modloss_nn.0.bert.layer.0.attention.output.dense.bias', 'modloss_nn.0.bert.layer.0.attention.output.LayerNorm.weight', 'modloss_nn.0.bert.layer.0.attention.output.LayerNorm.bias', 'modloss_nn.0.bert.layer.0.intermediate.dense.weight', 'modloss_nn.0.bert.layer.0.intermediate.dense.bias', 'modloss_nn.0.bert.layer.0.output.dense.weight', 'modloss_nn.0.bert.layer.0.output.dense.bias', 'modloss_nn.0.bert.layer.0.output.LayerNorm.weight', 'modloss_nn.0.bert.layer.0.output.LayerNorm.bias', 'modloss_nn.1.nn.0.weight', 'modloss_nn.1.nn.0.bias', 'modloss_nn.1.nn.1.weight', 'modloss_nn.1.nn.2.weight', 'modloss_nn.1.nn.2.bias'] The following keys were missing: {'output_nn.nn.2.weight', 'output_nn.nn.2.bias'}\n" + ] + } + ], + "source": [ + "tune_mgr = FinetuneManager(\n", + " device=\"gpu\",\n", + " test_interval=3,\n", + " fragment_types=['b','y','c','a','x','z'],\n", + " max_charge=2)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "def calculate_similarity(precursor_df_a, precursor_df_b, intensity_df_a, intensity_df_b):\n", + "\n", + " _a_df = precursor_df_a[['precursor_idx', 'frag_start_idx', 'frag_stop_idx']].copy()\n", + " _b_df = precursor_df_b[['precursor_idx', 'frag_start_idx', 'frag_stop_idx']].copy()\n", + "\n", + " _merged_df = pd.merge(_a_df, _b_df, on='precursor_idx', suffixes=('_a', '_b'))\n", + " # keep only first precursor\n", + " _merged_df = _merged_df.drop_duplicates(subset='precursor_idx', keep='first')\n", + " similarity_list = []\n", + " predicted_columns = set(intensity_df_b.columns).intersection(intensity_df_a.columns)\n", + " predicted_columns = list(predicted_columns)\n", + " # only consider the predicted columns\n", + " intensity_df_a = intensity_df_a[predicted_columns]\n", + " intensity_df_b = intensity_df_b[predicted_columns]\n", + " \n", + "\n", + "\n", + " for i, (start_a, stop_a, start_b, stop_b) in enumerate(zip(_merged_df['frag_start_idx_a'], _merged_df['frag_stop_idx_a'], _merged_df['frag_start_idx_b'], _merged_df['frag_stop_idx_b'])):\n", + " observed_intensity = intensity_df_a.iloc[start_a:stop_a].values.flatten()\n", + " predicted_intensity = intensity_df_b.iloc[start_b:stop_b].values.flatten()\n", + "\n", + " similarity = np.dot(observed_intensity, predicted_intensity) / (np.linalg.norm(observed_intensity) * np.linalg.norm(predicted_intensity))\n", + " similarity_list.append({'similarity': similarity, 'index': i, 'precursor_idx': _merged_df.iloc[i]['precursor_idx']})\n", + "\n", + " return pd.DataFrame(similarity_list)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Performance on additional frag types\n", + "\n", + "The performance will extremely bad as expected since when we are starting from a pretrained model that is trained on a different fragment types, the output layer's weights are randomly initialized and we use the pretrained weights for everything else." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:48:50> Predicting MS2 ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 36/36 [00:03<00:00, 11.10it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['b_z1', 'b_z2', 'y_z1', 'y_z2', 'c_z1', 'c_z2', 'a_z1', 'a_z2', 'x_z1',\n", + " 'x_z2', 'z_z1', 'z_z2'],\n", + " dtype='object')\n", + "0.016662211069491333\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Similarity between observed and predicted MS2 spectra before fine-tuning')" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res = tune_mgr.predict_all(transfer_lib.precursor_df.copy(), predict_items=['ms2'])\n", + "\n", + "precursor_after_df = res['precursor_df']\n", + "fragment_mz_after_df = res['fragment_mz_df']\n", + "fragment_intensity_after_df = res['fragment_intensity_df']\n", + "similarity_after_df = calculate_similarity(precursor_after_df, transfer_lib.precursor_df, fragment_intensity_after_df, transfer_lib.fragment_intensity_df)\n", + "print(similarity_after_df['similarity'].median())\n", + "plt.scatter(similarity_after_df['index'], similarity_after_df['similarity'], s=0.1)\n", + "plt.xlabel('Index')\n", + "plt.ylabel('Similarity')\n", + "plt.title('Similarity between observed and predicted MS2 spectra before fine-tuning')" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 4565/4565 [00:01<00:00, 2298.87it/s]\n", + "100%|██████████| 2283/2283 [00:00<00:00, 2451.16it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:49:10> Model tested on validation dataset with the following metrics:\n", + "2024-12-30 23:49:10> l1_loss : 0.1145\n", + "2024-12-30 23:49:10> PCC-mean : -0.1060\n", + "2024-12-30 23:49:10> COS-mean : 0.0171\n", + "2024-12-30 23:49:10> SA-mean : 0.0109\n", + "2024-12-30 23:49:10> SPC-mean : -1.0849\n", + "2024-12-30 23:49:10> Fine-tuning MS2 model with the following settings:\n", + "2024-12-30 23:49:10> Train fraction: 0.70 Train size: 15978 \n", + "2024-12-30 23:49:10> Validation fraction: 0.20 Validation size: 4565 \n", + "2024-12-30 23:49:10> Test fraction: 0.10 Test size: 2283 \n", + "2024-12-30 23:49:17> Epoch 0 Lr: 0.00020 Training loss: 0.0795 validation loss: 0.1815\n", + "2024-12-30 23:49:31> Epoch 3 Lr: 0.00050 Training loss: 0.0297 validation loss: 0.0689\n", + "2024-12-30 23:49:48> Epoch 6 Lr: 0.00060 Training loss: 0.0189 validation loss: 0.0164\n", + "2024-12-30 23:50:04> Epoch 9 Lr: 0.00060 Training loss: 0.0151 validation loss: 0.0155\n", + "2024-12-30 23:50:20> Epoch 12 Lr: 0.00060 Training loss: 0.0148 validation loss: 0.0159\n", + "2024-12-30 23:50:37> Epoch 15 Lr: 0.00060 Training loss: 0.0139 validation loss: 0.0154\n", + "2024-12-30 23:50:52> Epoch 18 Lr: 0.00060 Training loss: 0.0143 validation loss: 0.0155\n", + "2024-12-30 23:51:08> Epoch 21 Lr: 0.00060 Training loss: 0.0128 validation loss: 0.0143\n", + "2024-12-30 23:51:25> Epoch 24 Lr: 0.00060 Training loss: 0.0128 validation loss: 0.0139\n", + "2024-12-30 23:51:42> Epoch 27 Lr: 0.00060 Training loss: 0.0122 validation loss: 0.0136\n", + "2024-12-30 23:51:59> Epoch 30 Lr: 0.00060 Training loss: 0.0130 validation loss: 0.0135\n", + "2024-12-30 23:52:15> Epoch 33 Lr: 0.00030 Training loss: 0.0114 validation loss: 0.0126\n", + "2024-12-30 23:52:31> Epoch 36 Lr: 0.00030 Training loss: 0.0110 validation loss: 0.0129\n", + "2024-12-30 23:52:48> Epoch 39 Lr: 0.00030 Training loss: 0.0109 validation loss: 0.0126\n", + "2024-12-30 23:53:03> Epoch 42 Lr: 0.00030 Training loss: 0.0110 validation loss: 0.0127\n", + "2024-12-30 23:53:19> Epoch 45 Lr: 0.00015 Training loss: 0.0109 validation loss: 0.0129\n", + "2024-12-30 23:53:36> Epoch 48 Lr: 0.00015 Training loss: 0.0104 validation loss: 0.0126\n", + "2024-12-30 23:53:46> Model tested on test dataset with the following metrics:\n", + "2024-12-30 23:53:46> l1_loss : 0.0122\n", + "2024-12-30 23:53:46> PCC-mean : 0.9462\n", + "2024-12-30 23:53:46> COS-mean : 0.9491\n", + "2024-12-30 23:53:46> SA-mean : 0.7961\n", + "2024-12-30 23:53:46> SPC-mean : -0.3072\n" + ] + } + ], + "source": [ + "\n", + "# Testing the ms2 finetuning on the transfer library\n", + "ms2_stats = tune_mgr.finetune_ms2(psm_df=transfer_lib.precursor_df.copy(), matched_intensity_df=transfer_lib.fragment_intensity_df.copy())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### performance after fine tuning\n", + "We can see a huge improvement after we have done finetuning for the whole model and trained the last layer so we can predict more fragment types than the one used in the pretrained model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:04:11> Predicting MS2 ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 36/36 [00:03<00:00, 11.96it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['b_z1', 'b_z2', 'y_z1', 'y_z2', 'c_z1', 'c_z2'], dtype='object')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\USER\\AppData\\Local\\Temp\\ipykernel_26272\\2151964994.py:22: RuntimeWarning: invalid value encountered in scalar divide\n", + " similarity = np.dot(observed_intensity, predicted_intensity) / (np.linalg.norm(observed_intensity) * np.linalg.norm(predicted_intensity))\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.9875111856175615\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Similarity between observed and predicted MS2 spectra after fine-tuning')" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res = tune_mgr.predict_all(transfer_lib.precursor_df.copy(), predict_items=[\"ms2\"])\n", + "\n", + "precursor_after_df = res[\"precursor_df\"]\n", + "fragment_mz_after_df = res[\"fragment_mz_df\"]\n", + "fragment_intensity_after_df = res[\"fragment_intensity_df\"]\n", + "similarity_after_df = calculate_similarity(\n", + " precursor_after_df,\n", + " transfer_lib.precursor_df,\n", + " fragment_intensity_after_df,\n", + " transfer_lib.fragment_intensity_df,\n", + ")\n", + "print(similarity_after_df[\"similarity\"].median())\n", + "plt.scatter(similarity_after_df[\"index\"], similarity_after_df[\"similarity\"], s=0.1)\n", + "plt.xlabel(\"Index\")\n", + "plt.ylabel(\"Similarity\")\n", + "plt.title(\"Similarity between observed and predicted MS2 spectra after fine-tuning\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# save model to disk\n", + "path_to_save = \"alphaDIA/transfer_weights\"\n", + "\n", + "tune_mgr.save_models(path_to_save)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading the model for prediction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:29:52> Device set to gpu\n", + "2024-12-30 23:29:54> The loaded weights are not strictly matched with the current model, some layers are still randomly initialized. Make sure to train the model or load different weights before prediction. The following keys had size mismatches: ['output_nn.nn.2.weight', 'output_nn.nn.2.bias'] The following keys were unexpected: ['modloss_nn.0.bert.layer.0.attention.self.query.weight', 'modloss_nn.0.bert.layer.0.attention.self.query.bias', 'modloss_nn.0.bert.layer.0.attention.self.key.weight', 'modloss_nn.0.bert.layer.0.attention.self.key.bias', 'modloss_nn.0.bert.layer.0.attention.self.value.weight', 'modloss_nn.0.bert.layer.0.attention.self.value.bias', 'modloss_nn.0.bert.layer.0.attention.output.dense.weight', 'modloss_nn.0.bert.layer.0.attention.output.dense.bias', 'modloss_nn.0.bert.layer.0.attention.output.LayerNorm.weight', 'modloss_nn.0.bert.layer.0.attention.output.LayerNorm.bias', 'modloss_nn.0.bert.layer.0.intermediate.dense.weight', 'modloss_nn.0.bert.layer.0.intermediate.dense.bias', 'modloss_nn.0.bert.layer.0.output.dense.weight', 'modloss_nn.0.bert.layer.0.output.dense.bias', 'modloss_nn.0.bert.layer.0.output.LayerNorm.weight', 'modloss_nn.0.bert.layer.0.output.LayerNorm.bias', 'modloss_nn.1.nn.0.weight', 'modloss_nn.1.nn.0.bias', 'modloss_nn.1.nn.1.weight', 'modloss_nn.1.nn.2.weight', 'modloss_nn.1.nn.2.bias'] The following keys were missing: {'output_nn.nn.2.weight', 'output_nn.nn.2.bias'}\n", + "2024-12-30 23:29:54> Predicting RT, MS2 and mobility\n", + "2024-12-30 23:29:54> Predicting RT ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 36/36 [00:02<00:00, 12.65it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:29:57> Predicting mobility ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 36/36 [00:02<00:00, 14.27it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:30:00> Predicting MS2 ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 36/36 [00:03<00:00, 11.39it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2024-12-30 23:30:03> Adding fragment mz information\n", + "2024-12-30 23:30:03> Adding fragment intensity information\n", + "2024-12-30 23:30:03> Adding precursor information\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.3532415056799123\n" + ] + } + ], + "source": [ + "from alphadia import libtransform, outputtransform\n", + "tune_mgr._normalize_intensity(transfer_lib.precursor_df, transfer_lib.fragment_intensity_df)\n", + "to_be_predicted = SpecLibBase()\n", + "to_be_predicted._precursor_df = transfer_lib.precursor_df.copy()\n", + "# ----------------- Verify that a warning is raised when using incorrect model -----------------\n", + "pept_deep_prediction = libtransform.PeptDeepPrediction(\n", + " fragment_mz=[200,2000],\n", + " fragment_types= ['b','y','c','a','x','z'],\n", + " max_fragment_charge=2,\n", + " )\n", + "pred = pept_deep_prediction.forward(to_be_predicted)\n", + "# calculate similarity\n", + "similarity_after_df = calculate_similarity(\n", + " pred.precursor_df,\n", + " transfer_lib.precursor_df,\n", + " pred.fragment_intensity_df,\n", + " transfer_lib.fragment_intensity_df,\n", + ")\n", + "print(f\"Median similarity for the prediction: {similarity_after_df['similarity'].median()}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "to_be_predicted = SpecLibBase()\n", + "to_be_predicted._precursor_df = transfer_lib.precursor_df.copy()\n", + "pept_deep_prediction = libtransform.PeptDeepPrediction(\n", + " fragment_mz=[200,2000],\n", + " fragment_types= ['b','y','c','a','x','z'],\n", + " peptdeep_model_path=path_to_save,\n", + " max_fragment_charge=2,\n", + " )\n", + "pred = pept_deep_prediction.forward(to_be_predicted)\n", + "# calculate similarity\n", + "similarity_after_df = calculate_similarity(\n", + " pred.precursor_df,\n", + " transfer_lib.precursor_df,\n", + " pred.fragment_intensity_df,\n", + " transfer_lib.fragment_intensity_df,\n", + ")\n", + "print(f\"Median similarity for the prediction: {similarity_after_df['similarity'].median()}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "alpha", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}