From f9edfe4bf24d230f5fe85c1ed9c529d7425d5607 Mon Sep 17 00:00:00 2001 From: ekiernan <55763654+ekiernan@users.noreply.github.com> Date: Tue, 9 Jun 2020 15:47:42 -0400 Subject: [PATCH] Lk remove zarr readme (#350) Updated Optimus documentation for Zarr removal --- docs/matrix_format_spec.md | 16 ++++++++------ pipelines/optimus/Loom_schema.md | 11 +++++----- pipelines/optimus/Optimus_diagram.png | Bin 201130 -> 127035 bytes pipelines/optimus/Optimus_diagram.pptx | Bin 46527 -> 46322 bytes pipelines/optimus/README.md | 28 +++++++++++-------------- 5 files changed, 27 insertions(+), 28 deletions(-) diff --git a/docs/matrix_format_spec.md b/docs/matrix_format_spec.md index bf44006d8..e9cbf2dbe 100644 --- a/docs/matrix_format_spec.md +++ b/docs/matrix_format_spec.md @@ -1,7 +1,11 @@ -# Version 1.0 +| Zarr Deprecation Notice June 2020 | +| --- | +| The Zarr output has been deprecated and is no longer generated by skylab pipelines as of June 2020. | + +### Version 1.0 The version of the ZARR output can be identified by examining the `optimus_output_schema_version` attribute of the root node. Sematic versioning of the file schema should be used. -## Format +#### Format The secondary analysis pipelines shall write expression matrices and associated tabular metadata using the zarr version 2 DirectoryStore format. The format is specified in more detail [here](https://zarr.readthedocs.io/en/stable/spec/v2.html). @@ -24,15 +28,15 @@ Data are stored in the following chunked and compressed arrays: - gene_metadata_string ("aK~5-imJJ0tvP@Be)%T;veKd$s6?nRFfbV6VjtvSU=TZDVBokwNWeQQ z%}3vXU$EA4qCzl510>tPA1D@L%GNM2_&85Lum;H^z%2qW;vWR%A+URi$jriaC?r(z< zIvGU;G$;x5aMtCT0jsoue7!IK(_IuEAlwuVGOZNmI5mywxw4?MXbsPQv)=r8U zkSs}PB}>cAe_qeO7P-a=8?fpS5`*}^hkYOhh7H?^D3SkX(flPZ4<1?pOP)dOGMN88 z%#aEgHZuU)75-m4LLIh=@G4}JQycGpZX7k(6c{EtOQ_}YzfJZeK|m-ex(N=I#G_sX ztE(e()~hmK@w7*-Kwf)@b$Rd1u|6VcBk~I2@}3j_*eM z>>6mOvj;*BW}6ZJtK47d0z$(7jZ3z@fybcyVF_{Hd>I0{CEr!`t>#%CK1_&LW$eWF zkB(Rmb+RL$ar!V4l80aU&Hqb)KkXJIkntoQTI6bPGw$L#4-qRUMsb3R?f$z2#-1dw zGn!l#{P+J}l3xC2*xy{KM4S(M6>c%X+Lh+cmY-gfDu-Yy61nGwe`@*y)3d#btQW zm$qv!lpkjmIiZg^oaoxFv#wGZ(qWh|RoC334r8YEsugk#QV)qpbem?Z3+rM-S1U8W zb!Wa)r7ZrqT-GjD5?DIBWKBYx!#PG%VU`m_{=3r%6LeqUDE3yx zR;oWTpUzKOmdsS7_Ptv)HGqI){ziWTw@6TGw((vDVHMJ5U!4h=d@MJFYk@++` 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+| [optimus_v3.0.0](https://github.com/HumanCellAtlas/skylab/releases/tag/optimus_v3.0.0) | June 02, 2020 | [Elizabeth Kiernan](mailto:ekiernan@broadinstitute.org) | Please file GitHub issues in skylab or contact [Kylee Degatano](mailto:kdegatano@broadinstitute.org) | # Table of Contents - [Optimus Pipeline Overview](#optimus-pipeline-overview) @@ -33,7 +33,7 @@ ## Introduction to the Optimus Workflow -Optimus is a pipeline developed by the Data Coordination Platform (DCP) of the [Human Cell Atlas (HCA) Project](https://data.humancellatlas.org/) that supports processing of any 3' single-cell and single-nuclei expression data generated with the [10x Genomic v2 or v3 assay](https://www.10xgenomics.com/solutions/single-cell/). It is an alignment and transcriptome quantification pipeline that corrects cell barcodes, aligns reads to the genome, corrects Unique Molecular Identifiers (UMIs), generates an expression matrix in a UMI-aware manner, calculates summary metrics for genes and cells, detects empty droplets, returns read outputs in BAM format, and returns cell gene expression in numpy matrix, Zarr, and Loom file formats. Special care is taken to keep all reads that may be useful to the downstream user, such as unaligned reads or reads with uncorrectable barcodes. This design provides flexibility to the downstream user and allows for alternative filtering or leveraging the data for novel methodological development. +Optimus is a pipeline developed by the Data Coordination Platform (DCP) of the [Human Cell Atlas (HCA) Project](https://data.humancellatlas.org/) that supports processing of any 3' single-cell and single-nuclei expression data generated with the [10x Genomic v2 or v3 assay](https://www.10xgenomics.com/solutions/single-cell/). It is an alignment and transcriptome quantification pipeline that corrects cell barcodes, aligns reads to the genome, corrects Unique Molecular Identifiers (UMIs), generates an expression matrix in a UMI-aware manner, calculates summary metrics for genes and cells, detects empty droplets, returns read outputs in BAM format, and returns cell gene expression in numpy matrix and Loom file formats. Special care is taken to keep all reads that may be useful to the downstream user, such as unaligned reads or reads with uncorrectable barcodes. This design provides flexibility to the downstream user and allows for alternative filtering or leveraging the data for novel methodological development. Optimus has been validated for analyzing both [human](https://github.com/HumanCellAtlas/skylab/blob/master/benchmarking/optimus/optimus_report.rst) and [mouse](https://docs.google.com/document/d/1_3oO0ZQSrwEoe6D3GgKdSmAQ9qkzH_7wrE7x6_deL10/edit) data sets. More details about the human validation can be found in the [in the original file](https://docs.google.com/document/d/158ba_xQM9AYyu8VcLWsIvSoEYps6PQhgddTr9H0BFmY/edit). @@ -49,7 +49,7 @@ Optimus has been validated for analyzing both [human](https://github.com/HumanCe | Aligner | STAR (v.2.5.3a) | [Dobin, et al.,2013](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530905/) | | Transcript Quantification | Utilities for processing large-scale single cell datasets | [sctools](https://github.com/HumanCellAtlas/sctools) | Data Input File Format | File format in which sequencing data is provided | [FASTQ](https://academic.oup.com/nar/article/38/6/1767/3112533) | -| Data Output File Format | File formats in which Optimus output is provided | [BAM](http://samtools.github.io/hts-specs/), [Zarr version 2](https://zarr.readthedocs.io/en/stable/spec/v2.html), Python numpy arrays (internal), Loom (generated with [Loompy v.2.0.17)](http://loompy.org/) | +| Data Output File Format | File formats in which Optimus output is provided | [BAM](http://samtools.github.io/hts-specs/), Python numpy arrays (internal), Loom (generated with [Loompy v.3.0.6)](http://loompy.org/) | # Set-up @@ -113,7 +113,7 @@ Overall, the workflow: 6. Calculates summary metrics 7. Produces a UMI-aware expression matrix 8. Detects empty droplets -9. Returns a GA4GH compliant BAM and an expression matrix in Zarr or Loom formats +9. Returns a GA4GH compliant BAM and an expression matrix in Loom formats The tools each Optimus task employs are detailed in the following table: @@ -170,7 +170,7 @@ UMIs are designed to distinguish unique transcripts present in the cell at lysis ### 6. Summary Metric Calculation -The [Metrics](https://github.com/HumanCellAtlas/skylab/blob/master/library/tasks/SequenceDataWithMoleculeTagMetrics.wdl) task uses [sctools](https://github.com/HumanCellAtlas/sctools) to calculate summary metrics which help assess the quality of the data output each time this pipeline is run. These metrics are included in the Zarr and Loom output files. A detailed list of these metrics is found in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). +The [Metrics](https://github.com/HumanCellAtlas/skylab/blob/master/library/tasks/SequenceDataWithMoleculeTagMetrics.wdl) task uses [sctools](https://github.com/HumanCellAtlas/sctools) to calculate summary metrics which help assess the quality of the data output each time this pipeline is run. These metrics are included in the Loom output file. A detailed list of these metrics is found in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). ### 7. Expression Matrix Construction @@ -178,7 +178,7 @@ The Optimus [CreateCountMatrix](https://github.com/HumanCellAtlas/skylab/blob/ma ### 8. Identification of Empty Droplets -Empty droplets are lipid droplets that did not encapsulate a cell during 10x sequencing, but instead acquired cell-free RNA (secreted RNA or RNA released during cell lysis) from the solution in which the cells resided ([Lun, et al., 2018](https://www.ncbi.nlm.nih.gov/pubmed/?term=30902100). This ambient RNA can serve as a substrate for reverse transcription, leading to a small number of background reads. The Optimus pipeline calls the [RunEmptyDrops](https://github.com/HumanCellAtlas/skylab/blob/master/library/tasks/RunEmptyDrops.wdl) task which uses the [dropletUtils v.0.1.1](http://bioconductor.org/packages/release/bioc/html/DropletUtils.html) R package to flag cell barcodes that represent empty droplets rather than cells. A cell will be flagged if it contains fewer than 100 molecules. These metrics are stored in the output Zarr and Loom files. Details of all the metrics included in the final output files can be found in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). +Empty droplets are lipid droplets that did not encapsulate a cell during 10x sequencing, but instead acquired cell-free RNA (secreted RNA or RNA released during cell lysis) from the solution in which the cells resided ([Lun, et al., 2018](https://www.ncbi.nlm.nih.gov/pubmed/?term=30902100). This ambient RNA can serve as a substrate for reverse transcription, leading to a small number of background reads. The Optimus pipeline calls the [RunEmptyDrops](https://github.com/HumanCellAtlas/skylab/blob/master/library/tasks/RunEmptyDrops.wdl) task which uses the [dropletUtils v.0.1.1](http://bioconductor.org/packages/release/bioc/html/DropletUtils.html) R package to flag cell barcodes that represent empty droplets rather than cells. A cell will be flagged if it contains fewer than 100 molecules. These metrics are stored in the output Loom file. Details of all the metrics included in the final output files can be found in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). | Warning: RunEmptyDrops output not included for single-nuclei data | | --- | @@ -203,20 +203,17 @@ The following table lists the output files produced from the pipeline. For sampl | matrix_col_index | sparse_counts_col_index.npy | Index of genes in expression matrix | Numpy array index | | cell_metrics | merged-cell-metrics.csv.gz | cell metrics | compressed csv | Matrix of metrics by cells | | gene_metrics | merged-gene-metrics.csv.gz | gene metrics | compressed csv | Matrix of metrics by genes | -| zarr_output_files | {unique_id}.zarr!.zattrs | Zarr | Array | | loom_output_file | output.loom | Loom | Loom | Loom file with expression data and metadata | N/A | -The Zarr array is the default output. The Zarr schema version is detailed in the array as 'optimus_output_schema_version'. The schema version is specified to the Zarr using the [create_zarr_optimus.py](https://github.com/HumanCellAtlas/skylab/blob/master/docker/zarr-output/create_zarr_optimus.py) script. +The Loom is the default output. See the [create_loom_optimus.py](https://github.com/HumanCellAtlas/skylab/blob/master/docker/loom-output/create_loom_optimus.py) for the detailed code. -The Loom file is an optional output that is specified in the "meta" section of the [Optimus workflow](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Optimus.wdl) with the following boolean command: -`Boolean output_loom = false` - -To obtain a Loom file, the boolean parameter "false" must be changed to "true". - -All final Zarr and Loom outputs contain the unnormalized (unfiltered), UMI-corrected expression matrices, as well as the gene and cell metrics detailed in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). +The final Loom output contains the unnormalized (unfiltered), UMI-corrected expression matrices, as well as the gene and cell metrics detailed in the [Loom_schema documentation](https://github.com/HumanCellAtlas/skylab/blob/master/pipelines/optimus/Loom_schema.md). +| Zarr Array Deprecation Notice June 2020 | +| --- | +| Please note that we have deprecated the previously used Zarr array output. The pipeline now uses the Loom file format as the default output. | # Versioning @@ -256,8 +253,7 @@ There are four example configuration JSON files available for you to test the pi

    What outputs are expected if my sample has been sequenced over multiple lanes?
    -The Optimus pipeline is a single sample pipeline, but it can accept multiple FASTQ files if a sample is sequenced across lanes. In this case, the pipeline will merge the results from each lane into single output files. There will only be one merged file for each output type (i.e one Zarr array, one Loom, etc.). If you would like to view an example configuration file for a multi-lane dataset, please see the
    mouse_v2_example.json . Additionally, you can view sample outputs in the Optimus featured workspace on Terra: https://app.terra.bio/#workspaces/featured-workspaces-hca/HCA_Optimus_Pipeline. +The Optimus pipeline is a single sample pipeline, but it can accept multiple FASTQ files if a sample is sequenced across lanes. In this case, the pipeline will merge the results from each lane into single output files. There will only be one merged file for each output type (i.e one Loom, etc.). If you would like to view an example configuration file for a multi-lane dataset, please see the mouse_v2_example.json . Additionally, you can view sample outputs in the Optimus featured workspace on Terra: https://app.terra.bio/#workspaces/featured-workspaces-hca/HCA_Optimus_Pipeline.
    -