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Polish the get-started guide #97

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merged 3 commits into from
Nov 22, 2024
Merged

Polish the get-started guide #97

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4b6168e
Polish the get-started guide
falexwolf Nov 21, 2024
cbcb3ad
Also make title consistent with tab name
falexwolf Nov 21, 2024
ad6495d
Tidy and minor fixes
lazappi Nov 22, 2024
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19 changes: 11 additions & 8 deletions vignettes/laminr.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
title: "Get started"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Getting started}
%\VignetteIndexEntry{Get started}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
---
Expand All @@ -18,7 +18,7 @@ knitr::opts_chunk$set(
submit_eval <- laminr:::.get_user_settings()$handle != "testuser1"
```

This vignettes introduce the basic workflow.
This vignette introduces the basic **{laminr}** workflow.

# Setup

Expand All @@ -41,8 +41,9 @@ lamin connect <owner>/<name>
```

This instance acts as the default instance for everything that follows.
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I hope this is clear enough. If another sentence is needed please add.

Any new records or other changes will be added here.

# Start an R session
# Connect to the default instance
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I find it problematic to say "connect to the default instance" in this heading, @lazappi, because that just happened 3 lines above on the command line. Don't you agree?

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This is how it reads now:

image

I felt that if one calls it "Start an R session" and then people see that they create an instance object by calling connect() in R one avoids calling two different things (CLI connect vs R connect()) with the same name "connect to the default instance".

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Fixed in new PR.


Load **{laminr}** to get started.

Expand All @@ -57,7 +58,7 @@ db <- connect()
db
```

It allows you to manage all datasets & metadata entities with auto-complete.
It is used to manage all datasets and metadata entities.

# Track data lineage
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People should get used to calling track() first thing.


Expand Down Expand Up @@ -86,7 +87,8 @@ cellxgene

# Download a dataset

Artifacts are objects that bundle data and associated metadata. An artifact can be any file or folder but is typically a dataset.
Artifacts are objects that bundle data and associated metadata.
An artifact can be any file or folder but is typically a dataset.

```{r get-artifact}
artifact <- cellxgene$Artifact$get("7dVluLROpalzEh8mNyxk")
Expand All @@ -98,7 +100,7 @@ artifact

You can view detailed information about this dataset on LaminHub: https://lamin.ai/laminlabs/cellxgene/artifact/7dVluLROpalzEh8mNyxk.

You can search & query more datasets here: https://lamin.ai/laminlabs/cellxgene/artifacts.
You can search and query more CELLxGENE datasets here: https://lamin.ai/laminlabs/cellxgene/artifacts.
</div>

To download the dataset and load it into memory, run:
Expand All @@ -114,7 +116,6 @@ This artifact contains an [`AnnData`](https://anndata.readthedocs.io) object.
**Tip**

If you prefer a path to a local file or folder, call `path <- artifact$cache()`.

</div>

# Work with the data
Expand All @@ -126,10 +127,12 @@ Here, marker genes are calculated for each of the provided cell type labels usin
# Create a Seurat object
seurat <- SeuratObject::CreateSeuratObject(
counts = as(Matrix::t(adata$X), "CsparseMatrix"),
meta.data = adata$obs,
meta.data = adata$obs
)
# Set cell identities to the provided cell type annotation
SeuratObject::Idents(seurat) <- "cell_type"
# Normalise the data
seurat <- Seurat::NormalizeData(seurat)
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I thought that this let's peoples memory and storage explode; that's why I removed it. It'd be a bad experience if upload or compute etc. took long -- so keeping data small would be good.

If it's not actually an issue anymore, it's all good!

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Ignored in new PR.

# Test for marker genes (the output is a data.frame)
markers <- Seurat::FindAllMarkers(
seurat,
Expand Down
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