Pre-processing with Alevin - Part 1


StepAnnotation
Step 1: Input dataset
select at runtime
Step 2: Input dataset
select at runtime
Step 3: Input dataset
select at runtime
Step 4: Input dataset
select at runtime
Step 5: GTF2GeneList
Output dataset 'output' from step 1
gene
gene_id
True
gene_id,gene_name,mito
True
True
mt,mitochondrion_genome,mito,m,chrM,chrMt
mt_trna,mt_rrna,mt_trna_pseudogene
False
Step 6: GTF2GeneList
Output dataset 'output' from step 1
transcript
transcript_id
True
transcript_id,gene_id
True
False
True
Output dataset 'output' from step 3
transcript_id
Step 7: Alevin
Use one from the history
Salmon index:
Output dataset 'fasta_output' from step 6
31
False
Paired-end
Output dataset 'output' from step 4
Output dataset 'output' from step 2
Mates are oriented toward each other (I = inward)
read comes from the reverse strand (SR)
DropSeq Single Cell protocol
Output dataset 'feature_annotation' from step 6
True
Optional commands:
select at runtime
False
select at runtime
select at runtime
False
True
False
True
Not available.
Not available.
Not available.
Not available.
1.0
Not available.
Not available.
3
Step 8: Alevin
Use one from the history
Salmon index:
Output dataset 'fasta_output' from step 6
31
False
Paired-end
Output dataset 'output' from step 4
Output dataset 'output' from step 2
Mates are oriented toward each other (I = inward)
read comes from the reverse strand (SR)
DropSeq Single Cell protocol
Output dataset 'feature_annotation' from step 6
True
Optional commands:
select at runtime
False
select at runtime
select at runtime
False
True
False
True
Not available.
Not available.
Not available.
Not available.
Not available.
Not available.
Not available.
Not available.
Step 9: salmonKallistoMtxTo10x
Output dataset 'quants_mat.mtx' from step 7
Output dataset 'quants_mat_cols.txt' from step 7
Output dataset 'quants_mat_rows.txt' from step 7
Empty.
Step 10: Droplet barcode rank plot
False
Output dataset 'raw_cb_frequency.txt' from step 8
Barcode rank plot (raw barcode frequencies)
50
1.5
Step 11: Droplet barcode rank plot
True
Output dataset 'quants_mat.mtx' from step 8
True
Barcode rank plot (Alevin-processed)
50
1.5
Step 12: Join two Datasets
Output dataset 'genes_out' from step 9
1
Output dataset 'feature_annotation' from step 5
1
Yes
Yes
No
No
Step 13: Cut
c1,c4,c5
Tab
Output dataset 'out_file1' from step 12
Step 14: DropletUtils Read10x
Output dataset 'matrix_out' from step 9
Output dataset 'out_file1' from step 13
Output dataset 'barcodes_out' from step 9
False
Step 15: DropletUtils emptyDrops
Output dataset 'output_rds' from step 14
5
1000
0.01
False
Not available.
Not available.
True
Step 16: DropletUtils emptyDrops
Output dataset 'output_rds' from step 14
100
1000
0.01
False
Not available.
Not available.
True
Step 17: SCEasy convert
SingleCellExperiment to AnnData
Output dataset 'output_rdata' from step 15
counts