scamp configuration
These notes illustrate how to configure an analysis using {scamp}. Detailed descriptions of the parameters can be found in the modules or workflows documentation.
Analysis configuration
A parameters YAML file is used to described all aspects of a project and should serve as a record for parameters used in the pipeline. It will be passed to Nextflow as a parameter using --scamp_file
.
The structure of parameters file allows aspects of a project to be recorded alongside analysis parameters that can be specified for multiple datasets in a plain text and human-readable format. Parameter keys that begin with underscores are reserved by {scamp} and should not be used in other keys. At the first level, the project (_project
), genome (_genome
), common dataset parameters (_defaults
) and dataset (_dataset
) stanzas are specified. Within the datasets stanza, datasets can be freely (but sensibly) named.
Example configuration file
In this example for a scRNA-seq project, there are four datasets that will be quantified against mouse using the Cell Ranger mm10 reference from which Seurat objects will be prepared. To keep the file clear I have assumed symlinks are available in an inputs
directory to other parts of the filesystem. The inputs/primary_data
is a symlink to ASF’s outputs for this project and inputs/10x_indexes
is a symlink to the communal 10X indexes resource.
1_project:
2 lab: morisn
3 scientist: christopher.cooke
4 lims id: SC22034
5 babs id: nm322
6 type: 10X-3prime
7
8_genome:
9 organism: mus musculus
10 assembly: mm10
11 ensembl release: 98
12 fasta file: inputs/10x_indexes/refdata-gex-mm10-2020-A/fasta/genome.fa
13 fasta index file: inputs/10x_indexes/refdata-gex-mm10-2020-A/fasta/genome.fa.fai
14 gtf file: inputs/10x_indexes/refdata-gex-mm10-2020-A/genes/genes.gtf
15
16_defaults:
17 fastq paths:
18 - inputs/primary_data/220221_A01366_0148_AH7HYGDMXY/fastq
19 - inputs/primary_data/220310_A01366_0156_AH5YTYDMXY/fastq
20 - inputs/primary_data/220818_A01366_0266_BHCJK7DMXY/fastq
21 - inputs/primary_data/230221_A01366_0353_AHNH37DSX5/fastq
22 feature types:
23 Gene Expression:
24 - COO4671A1
25 - COO4671A2
26 - COO4671A3
27 - COO4671A4
28 feature identifiers: name
29 workflows:
30 - quantification/cell ranger
31 - seurat/prepare/cell ranger
32 index path: inputs/10x_indexes/refdata-cellranger-mm10-3.0.0
33
34_datasets:
35 stella 120h rep1:
36 description: STELLA sorting at 120 hours
37 limsid: COO4671A1
38 dataset tag: ST120R1
39
40 pecam1 120h rep1:
41 description: PECAM1 sorting at 120 hours
42 limsid: COO4671A2
43 dataset tag: P120R1
44
45 ssea1 120h rep1:
46 description: SSEA1 sorting at 120 hours
47 limsid: COO4671A3
48 dataset tag: SS120R1
49
50 blimp1 + ssea1 120h rep1:
51 description: BLIMP1 and SSEA1 sorting at 120 hours
52 limsid: COO4671A4
53 dataset tag: BS120R1
1_project:
2 lab: guillemotf
3 scientist: sara.ahmeddeprado
4 lims id: SC22051
5 babs id: sa145
6 type: 10X-Multiomics
7
8_genome:
9 assembly: mm10 + mCherry
10 organism: mus musculus
11 ensembl release: 98
12 non-nuclear contigs:
13 - chrM
14 fasta path: inputs/fastas
15 gtf path: inputs/gtfs
16
17_defaults:
18 fastq paths:
19 - inputs/primary_data/220406_A01366_0169_AHC3HVDMXY/fastq
20 - inputs/primary_data/220407_A01366_0171_AH3W3LDRX2/fastq
21 - inputs/primary_data/220420_A01366_0179_BH72WWDMXY/fastq
22 - inputs/primary_data/220422_A01366_0180_BHJLLNDSX3/fastq
23 feature types:
24 Gene Expression:
25 - AHM4688A1
26 - AHM4688A2
27 - AHM4688A3
28 Chromatin Accessibility:
29 - AHM4688A4
30 - AHM4688A5
31 - AHM4688A6
32 feature identifiers: name
33 workflows:
34 - quantification/cell ranger arc
35 - seurat/prepare/cell ranger arc
36
37_datasets:
38 8 weeks sample1:
39 description: 8 weeks old, replicate 1
40 limsid:
41 - AHM4688A1
42 - AHM4688A4
43 dataset tag: 8WS1
44
45 8 weeks sample2:
46 description: 8 weeks old, replicate 2
47 limsid:
48 - AHM4688A2
49 - AHM4688A5
50 dataset tag: 8WS2
51
52 8 weeks sample3:
53 description: 8 weeks old, replicate 3
54 limsid:
55 - AHM4688A3
56 - AHM4688A6
57 dataset tag: 8WS3
1_project:
2 lab: morisn
3 scientist: christopher.cooke
4 lims id: SC22034
5 babs id: nm322
6 type: 10X-3prime
7
8_genome:
9 organism: mus musculus
10 assembly: mm10
11 ensembl release: 98
12 fasta file: inputs/10x_indexes/refdata-gex-mm10-2020-A/fasta/genome.fa
13 fasta index file: inputs/10x_indexes/refdata-gex-mm10-2020-A/fasta/genome.fa.fai
14 gtf file: inputs/10x_indexes/refdata-gex-mm10-2020-A/genes/genes.gtf
15
16_defaults:
17 fastq paths:
18 - inputs/primary_data/220221_A01366_0148_AH7HYGDMXY/fastq
19 - inputs/primary_data/220310_A01366_0156_AH5YTYDMXY/fastq
20 - inputs/primary_data/220818_A01366_0266_BHCJK7DMXY/fastq
21 - inputs/primary_data/230221_A01366_0353_AHNH37DSX5/fastq
22 feature types:
23 Gene Expression:
24 - COO4671A1
25 - COO4671A2
26 - COO4671A3
27 - COO4671A4
28 feature identifiers: name
29 workflows:
30 - seurat/prepare/cell ranger
31 index path: inputs/10x_indexes/refdata-cellranger-mm10-3.0.0
32
33_datasets:
34 stella 120h rep1:
35 description: STELLA sorting at 120 hours
36 limsid: COO4671A1
37 dataset tag: ST120R1
38 quantification path: results/quantification/cell_ranger/outs/stella_120h_rep1
39 quantification method: cell ranger
40
41 pecam1 120h rep1:
42 description: PECAM1 sorting at 120 hours
43 limsid: COO4671A2
44 dataset tag: P120R1
45 quantification path: results/quantification/cell_ranger/outs/pecam1_120h_rep1
46 quantification method: cell ranger
47
48 ssea1 120h rep1:
49 description: SSEA1 sorting at 120 hours
50 limsid: COO4671A3
51 dataset tag: SS120R1
52 quantification path: results/quantification/cell_ranger/outs/ssea1_120h_rep1
53 quantification method: cell ranger
54
55 blimp1 + ssea1 120h rep1:
56 description: BLIMP1 and SSEA1 sorting at 120 hours
57 limsid: COO4671A4
58 dataset tag: BS120R1
59 quantification path: results/quantification/cell_ranger/outs/blimp1_ssea1_120h_rep1
60 quantification method: cell ranger
_project
includes information about the project rather than parameters that should be applied to datasets. Most of the information in this stanza can be extracted from a path on Nemo and/or the LIMS.
The _genome
stanza is static across most projects though the ensembl release
is tied to any index against which the data is aligned or quantified (etc).
_defaults
describes parameters that will be aggregated into every dataset in the _datasets
stanza of the project, with the dataset-level parameter taking precedence. (So we don’t have a big copy/paste list of parameters). Depending on the analysis workflows, different keys will be expected. In this example we are going to quantify expression of a scRNA-seq dataset so we need to know where the FastQ files are in the file system. The paths (not files) are specified here with fastq paths
. The feature_identifiers
will be used when the Seurat object is created; specifying “names” will use the gene names (rather than Ensembl identifiers) as feature names. The default parameters stanza typically contains a set of analysis workflows, using the workflows
key. This curated list of keywords identifies which workflows should be applied to the dataset(s). In the example we specify two workflows: quantification by Cell Ranger and Seurat object creation. The order of the workflows is not important. The keywords to include can be found in the workflows documentation.
Each dataset is described in _datasets
. Dataset stanzas must have unique names and ideally not contain odd characters. {scamp} will try to make the key directory-safe, however.