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Linearham's dependencies are described in the Dockerfile.
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We recommend that you run linearham inside a Docker container, since this will make installation much easier (if you're new to Docker, [read this](http://erick.matsen.org/2018/04/19/docker.html)).
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However, you can also install the dependencies by hand, in which case you should clone the repository and run each command in the [Dockerfile](https://github.com/matsengrp/linearham/blob/edit-readme/Dockerfile) that's on a line starting with `RUN` (treat `WORKDIR` as `cd`).
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However, you can also install the dependencies by hand, in which case you should clone the repository and run each command in the [Dockerfile](https://github.com/matsengrp/linearham/blob/main/Dockerfile) that's on a line starting with `RUN` (treat `WORKDIR` as `cd`).
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The more similar your system is to that described by the Dockerfile's `FROM` line (at the moment, debian), the easier this will be.
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#### Using Docker
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## Running linearham
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All linearham actions are run using scons in the main linearham directory.
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Available actions are `--run-partis`, `--run-linearham`, and `--build-partis-linearham`.
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Available actions are `--run-partis`, `--run-linearham`, and `--build`.
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Note that because of the way scons parses arguments, you must always use an `=` sign in all args: `--arg=val`.
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For the same reason, you also have to spell args exactly right, e.g. writing `--arg-nam` instead of `--arg-name` will silently ignore it.
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@@ -142,9 +142,9 @@ Other linearham-related arguments:
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For the arguments that can be specified as a (`,`-separated) list (see middle column), linearham will run revbayes separately, writing to separate nested output directories, for all combinations of all such parameters.
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For more information on these arguments, run `scons --help`.
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#### `--build-partis-linearham`
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#### `--build`
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This compiles linearham, partis, and other dependencies.
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This compiles linearham and other dependencies.
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You'll only need to run this if you've either modified some source code or you're installing without docker.
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## Run steps
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| get linearham info |`lib/partis/bin/partis get-linearham-info`| reformat the information in all annotations in the partis output file for use by subsequent linearham steps, writes to `partis_run.yaml`|
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| select single cluster |`scripts/parse_cluster.py`| pull annotation for single specified cluster out of `partis_run.yaml`, and write it to `cluster.yaml` and its sequences to `cluster_seqs.fasta`|
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| make revbayes input |`scripts/generate_revbayes_rev_file.py`| use seqs in `cluster_seqs.fasta` and template revbayes config `templates/revbayes_template.rev` to write revbayes config for this run to `revbayes_run.rev`|
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| run revbayes |`lib/revbayes/projects/cmake/rb`| run revbayes with config file `revbayes_run.rev`, writing output to `revbayes_run.stdout.log`. This step is usually by far the slowest; you can adjust e.g. the mcmc options above to trade off speed for confidence/accuracy. |
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| run revbayes |`rb`| run revbayes with config file `revbayes_run.rev`, writing output to `revbayes_run.stdout.log`. This step is usually by far the slowest; you can adjust e.g. the mcmc options above to trade off speed for confidence/accuracy. |
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| run phylo hmm |`_build/linearham/linearham --pipeline`| run actual linearham phylo hmm, using `cluster.yaml`, `<--parameter-dir>`, and `revbayes_run.trees` to write `lh_revbayes_run.trees`|
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| collect run statistics |`scripts/run_bootstrap_asr_ess.R`| collects info from `lh_revbayes_run.trees` and `cluster_seqs.fasta` to write three output files: `linearham_run.{trees,log,ess}`|
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| calculate naive seq stats |`scripts/tabulate_naive_probs.py`| collect info from `linearham_run.trees` to write `aa_naive_seqs.{png,fasta,dnamap}`|
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