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<div class="section" id="usage"> |
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<h1>Usage<a class="headerlink" href="#usage" title="Permalink to this headline">¶</a></h1> |
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<div class="section" id="quick-start"> |
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<h2>Quick Start<a class="headerlink" href="#quick-start" title="Permalink to this headline">¶</a></h2> |
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<div class="section" id="predict-a-new-network-using-a-trained-model"> |
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<h3>Predict a new network using a trained model<a class="headerlink" href="#predict-a-new-network-using-a-trained-model" title="Permalink to this headline">¶</a></h3> |
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<p>Pre-trained models can be downloaded from [TBD]. |
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Candidate pairs should be in tab-separated (<code class="docutils literal notranslate"><span class="pre">.tsv</span></code>) format with no header, and columns for [protein name 1], [protein name 2]. |
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Optionally, a third column with [label] can be provided, so predictions can be made using training or test data files (but the label will not affect the predictions).</p> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>dscript predict --pairs <span class="o">[</span>input data<span class="o">]</span> --seqs <span class="o">[</span>sequences, .fasta format<span class="o">]</span> --model <span class="o">[</span>model file<span class="o">]</span> |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="embed-sequences-with-language-model"> |
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<h3>Embed sequences with language model<a class="headerlink" href="#embed-sequences-with-language-model" title="Permalink to this headline">¶</a></h3> |
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<p>Sequences should be in <code class="docutils literal notranslate"><span class="pre">.fasta</span></code> format.</p> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>dscript embed --seqs <span class="o">[</span>sequences<span class="o">]</span> --outfile <span class="o">[</span>embedding file<span class="o">]</span> |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="train-and-save-a-model"> |
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<h3>Train and save a model<a class="headerlink" href="#train-and-save-a-model" title="Permalink to this headline">¶</a></h3> |
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<p>Training and validation data should be in tab-separated (<code class="docutils literal notranslate"><span class="pre">.tsv</span></code>) format with no header, and columns for [protein name 1], [protein name 2], [label].</p> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>dscript train --train <span class="o">[</span>training data<span class="o">]</span> --val <span class="o">[</span>validation data<span class="o">]</span> --embedding <span class="o">[</span>embedding file<span class="o">]</span> --save-prefix <span class="o">[</span>prefix<span class="o">]</span> |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="evaluate-a-trained-model"> |
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<h3>Evaluate a trained model<a class="headerlink" href="#evaluate-a-trained-model" title="Permalink to this headline">¶</a></h3> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>dscript <span class="nb">eval</span> --model <span class="o">[</span>model file<span class="o">]</span> --test <span class="o">[</span><span class="nb">test</span> data<span class="o">]</span> --embedding <span class="o">[</span>embedding file<span class="o">]</span> --outfile <span class="o">[</span>result file<span class="o">]</span> |
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</pre></div> |
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</div> |
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</div> |
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</div> |
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<div class="section" id="prediction"> |
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<h2>Prediction<a class="headerlink" href="#prediction" title="Permalink to this headline">¶</a></h2> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>usage: dscript predict <span class="o">[</span>-h<span class="o">]</span> --pairs PAIRS --model MODEL <span class="o">[</span>--seqs SEQS<span class="o">]</span> |
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<span class="o">[</span>--embeddings EMBEDDINGS<span class="o">]</span> <span class="o">[</span>-o OUTFILE<span class="o">]</span> <span class="o">[</span>-d DEVICE<span class="o">]</span> |
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<span class="o">[</span>--thresh THRESH<span class="o">]</span> |
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Make new predictions with a pre-trained model. One of --seqs and --embeddings is required. |
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optional arguments: |
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-h, --help show this <span class="nb">help</span> message and <span class="nb">exit</span> |
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--pairs PAIRS Candidate protein pairs to predict |
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--model MODEL Pretrained Model |
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--seqs SEQS Protein sequences in .fasta format |
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--embeddings EMBEDDINGS |
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h5 file with embedded sequences |
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-o OUTFILE, --outfile OUTFILE |
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File <span class="k">for</span> predictions |
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-d DEVICE, --device DEVICE |
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Compute device to use |
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--thresh THRESH Positive prediction threshold - used to store contact |
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maps and predictions in a separate file. <span class="o">[</span>default: |
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<span class="m">0</span>.5<span class="o">]</span> |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="embedding"> |
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<h2>Embedding<a class="headerlink" href="#embedding" title="Permalink to this headline">¶</a></h2> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>usage: dscript embed <span class="o">[</span>-h<span class="o">]</span> --seqs SEQS --outfile OUTFILE <span class="o">[</span>-d DEVICE<span class="o">]</span> |
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Generate new embeddings using pre-trained language model |
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optional arguments: |
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-h, --help show this <span class="nb">help</span> message and <span class="nb">exit</span> |
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--seqs SEQS Sequences to be embedded |
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--outfile OUTFILE h5 file to write results |
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-d DEVICE, --device DEVICE |
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Compute device to use |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="training"> |
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<h2>Training<a class="headerlink" href="#training" title="Permalink to this headline">¶</a></h2> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>usage: dscript train <span class="o">[</span>-h<span class="o">]</span> --train TRAIN --val VAL --embedding EMBEDDING |
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<span class="o">[</span>--augment<span class="o">]</span> <span class="o">[</span>--projection-dim PROJECTION_DIM<span class="o">]</span> |
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<span class="o">[</span>--dropout-p DROPOUT_P<span class="o">]</span> <span class="o">[</span>--hidden-dim HIDDEN_DIM<span class="o">]</span> |
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<span class="o">[</span>--kernel-width KERNEL_WIDTH<span class="o">]</span> <span class="o">[</span>--use-w<span class="o">]</span> |
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<span class="o">[</span>--pool-width POOL_WIDTH<span class="o">]</span> |
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<span class="o">[</span>--negative-ratio NEGATIVE_RATIO<span class="o">]</span> |
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<span class="o">[</span>--epoch-scale EPOCH_SCALE<span class="o">]</span> <span class="o">[</span>--num-epochs NUM_EPOCHS<span class="o">]</span> |
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<span class="o">[</span>--batch-size BATCH_SIZE<span class="o">]</span> <span class="o">[</span>--weight-decay WEIGHT_DECAY<span class="o">]</span> |
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<span class="o">[</span>--lr LR<span class="o">]</span> <span class="o">[</span>--lambda LAMBDA_<span class="o">]</span> <span class="o">[</span>-o OUTFILE<span class="o">]</span> |
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<span class="o">[</span>--save-prefix SAVE_PREFIX<span class="o">]</span> <span class="o">[</span>-d DEVICE<span class="o">]</span> |
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<span class="o">[</span>--checkpoint CHECKPOINT<span class="o">]</span> |
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Train a new model |
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optional arguments: |
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-h, --help show this <span class="nb">help</span> message and <span class="nb">exit</span> |
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Data: |
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--train TRAIN Training data |
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--val VAL Validation data |
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--embedding EMBEDDING |
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h5 file with embedded sequences |
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--augment Set flag to augment data by adding <span class="o">(</span>B A<span class="o">)</span> <span class="k">for</span> all pairs |
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<span class="o">(</span>A B<span class="o">)</span> |
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Projection Module: |
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--projection-dim PROJECTION_DIM |
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Dimension of embedding projection layer <span class="o">(</span>default: <span class="m">100</span><span class="o">)</span> |
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--dropout-p DROPOUT_P |
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Parameter p <span class="k">for</span> embedding dropout layer <span class="o">(</span>default: <span class="m">0</span>.5<span class="o">)</span> |
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Contact Module: |
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--hidden-dim HIDDEN_DIM |
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Number of hidden units <span class="k">for</span> comparison layer in contact |
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prediction <span class="o">(</span>default: <span class="m">50</span><span class="o">)</span> |
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--kernel-width KERNEL_WIDTH |
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Width of convolutional filter <span class="k">for</span> contact prediction |
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<span class="o">(</span>default: <span class="m">7</span><span class="o">)</span> |
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Interaction Module: |
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--use-w Use weight matrix in interaction prediction model |
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--pool-width POOL_WIDTH |
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Size of max-pool in interaction model <span class="o">(</span>default: <span class="m">9</span><span class="o">)</span> |
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Training: |
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--negative-ratio NEGATIVE_RATIO |
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Number of negative training samples <span class="k">for</span> each positive |
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training sample <span class="o">(</span>default: <span class="m">10</span><span class="o">)</span> |
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--epoch-scale EPOCH_SCALE |
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Report heldout performance every this many epochs |
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<span class="o">(</span>default: <span class="m">5</span><span class="o">)</span> |
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--num-epochs NUM_EPOCHS |
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Number of epochs <span class="o">(</span>default: <span class="m">100</span><span class="o">)</span> |
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--batch-size BATCH_SIZE |
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Minibatch size <span class="o">(</span>default: <span class="m">25</span><span class="o">)</span> |
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--weight-decay WEIGHT_DECAY |
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L2 regularization <span class="o">(</span>default: <span class="m">0</span><span class="o">)</span> |
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--lr LR Learning rate <span class="o">(</span>default: <span class="m">0</span>.001<span class="o">)</span> |
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--lambda LAMBDA_ Weight on the similarity objective <span class="o">(</span>default: <span class="m">0</span>.35<span class="o">)</span> |
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Output and Device: |
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-o OUTPUT, --output OUTPUT |
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Output file path <span class="o">(</span>default: stdout<span class="o">)</span> |
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--save-prefix SAVE_PREFIX |
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Path prefix <span class="k">for</span> saving models |
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-d DEVICE, --device DEVICE |
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Compute device to use |
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--checkpoint CHECKPOINT |
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Checkpoint model to start training from<span class="sb">``</span> |
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</pre></div> |
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</div> |
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</div> |
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<div class="section" id="evaluation"> |
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<h2>Evaluation<a class="headerlink" href="#evaluation" title="Permalink to this headline">¶</a></h2> |
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>usage: dscript <span class="nb">eval</span> <span class="o">[</span>-h<span class="o">]</span> --model MODEL --test TEST --embedding EMBEDDING |
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<span class="o">[</span>-o OUTFILE<span class="o">]</span> <span class="o">[</span>-d DEVICE<span class="o">]</span> |
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Evaluate a trained model |
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optional arguments: |
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-h, --help show this <span class="nb">help</span> message and <span class="nb">exit</span> |
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--model MODEL Trained prediction model |
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--test TEST Test Data |
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--embedding EMBEDDING |
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h5 file with embedded sequences |
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-o OUTFILE, --outfile OUTFILE |
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Output file to write results |
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-d DEVICE, --device DEVICE |
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Compute device to use |
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</pre></div> |
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