Tutorial
I assume you've already installed refgenie. In this tutorial I'll show you a few ways to use refgenie from the command line (commands that start with a !), and also some Python commands.
To start, initialize an empty refgenie configuration file from the shell and subscribe to the desired asset server:
!refgenie init -c refgenie.yaml -s http://rg.databio.org
Initialized genome configuration file: /Users/mstolarczyk/code/refgenie/docs_jupyter/refgenie.yaml
Created directories:
- /Users/mstolarczyk/code/refgenie/docs_jupyter/data
- /Users/mstolarczyk/code/refgenie/docs_jupyter/alias
Here's what it looks like:
!cat refgenie.yaml
config_version: 0.4
genome_folder: /Users/mstolarczyk/code/refgenie/docs_jupyter
genome_servers:
- http://rg.databio.org
genomes: null
!refgenie listr -c refgenie.yaml
Remote refgenie assets
Server URL: http://rg.databio.org
┏━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ genome ┃ assets ┃
┡━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ rCRSd │ fasta, bowtie2_index, bwa_index, hisat2_index, │
│ │ star_index, bismark_bt2_index │
│ hg18_cdna │ fasta, kallisto_index │
│ hs38d1 │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ hg38_cdna │ fasta, kallisto_index, salmon_index │
│ human_repeats │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ rn6_cdna │ fasta, kallisto_index, salmon_index │
│ mm10_cdna │ fasta, kallisto_index, salmon_index │
│ hg38_chr22 │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ hg38 │ fasta, gencode_gtf, ensembl_gtf, refgene_anno, │
│ │ fasta_txome, ensembl_rb, feat_annotation, │
│ │ suffixerator_index, cellranger_reference, bowtie2_index, │
│ │ bwa_index, tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index, salmon_partial_sa_index │
│ hg19_cdna │ fasta, kallisto_index, salmon_index │
│ human_rDNA │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ human_alu │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, bismark_bt2_index │
│ human_alphasat │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ mouse_chrM2x │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ t7 │ fasta, bowtie2_index │
│ mm10 │ fasta, gencode_gtf, ensembl_gtf, refgene_anno, │
│ │ fasta_txome, ensembl_rb, feat_annotation, │
│ │ suffixerator_index, cellranger_reference, bwa_index, │
│ │ bowtie2_index, hisat2_index, tallymer_index, star_index, │
│ │ bismark_bt2_index, salmon_partial_sa_index │
│ dm6 │ fasta, gencode_gtf, ensembl_gtf, refgene_anno, │
│ │ bowtie2_index │
│ hg18 │ fasta, gencode_gtf, fasta_txome, suffixerator_index, │
│ │ cellranger_reference, bwa_index, bowtie2_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index │
│ hg19 │ fasta, gencode_gtf, ensembl_gtf, refgene_anno, │
│ │ fasta_txome, ensembl_rb, feat_annotation, │
│ │ suffixerator_index, cellranger_reference, bwa_index, │
│ │ bowtie2_index, tallymer_index, hisat2_index, star_index, │
│ │ salmon_partial_sa_index, bismark_bt2_index │
│ rn6 │ fasta, ensembl_gtf, refgene_anno, fasta_txome, │
│ │ suffixerator_index, bwa_index, bowtie2_index, │
│ │ tallymer_index, hisat2_index, star_index, │
│ │ bismark_bt2_index, salmon_partial_sa_index │
│ hg38_noalt_decoy │ fasta, suffixerator_index, bowtie2_index, bwa_index, │
│ │ tallymer_index, hisat2_index, bismark_bt2_index │
│ mm10_primary │ fasta, bowtie2_index, bwa_index │
│ hg38_primary │ fasta, bowtie2_index, bwa_index │
│ hg38_mm10 │ fasta, bwa_index │
└──────────────────┴───────────────────────────────────────────────────────────┘
use refgenie listr -g <genome> for more detailed view
Now let's enter python and do some stuff.
import refgenconf
rgc = refgenconf.RefGenConf(filepath="refgenie.yaml")
Use pull to download one of the assets:
rgc.pull("mouse_chrM2x", "fasta", "default")
Output()
(['43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a', 'fasta', 'default'],
{'asset_path': 'fasta',
'asset_digest': '8dfe402f7d29d5b036dd8937119e4404',
'archive_digest': 'bfb7877ee114c61a17a50bd471de47a2',
'asset_size': '39.4KB',
'archive_size': '9.1KB',
'seek_keys': {'fasta': '43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a.fa',
'fai': '43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a.fa.fai',
'chrom_sizes': '43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a.chrom.sizes'},
'asset_parents': [],
'asset_children': ['43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/suffixerator_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/bowtie2_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/bwa_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/tallymer_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/hisat2_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/star_index:default',
'43f14ba8beed34d52edb244e26f193df6edbb467bd55d37a/bismark_bt2_index:default']},
'http://rg.databio.org')
Once it's downloaded, use seek to retrieve a path to it.
rgc.seek("mouse_chrM2x", "fasta")
'/Users/mstolarczyk/code/refgenie/docs_jupyter/alias/mouse_chrM2x/fasta/default/mouse_chrM2x.fa'
You can get the unique asset identifier with id()
rgc.id("mouse_chrM2x", "fasta")
'8dfe402f7d29d5b036dd8937119e4404'
Building and pulling from the command line
Here, we can build a fasta asset instead of pulling one. Back to the shell, we'll grab the Revised Cambridge Reference Sequence (human mitochondrial genome, because it's small):
!wget -O rCRSd.fa.gz http://big.databio.org/refgenie_raw/files.rCRSd.fasta.fasta
--2021-03-09 12:22:40-- http://big.databio.org/refgenie_raw/files.rCRSd.fasta.fasta
Resolving big.databio.org (big.databio.org)... 128.143.245.181, 128.143.245.182
Connecting to big.databio.org (big.databio.org)|128.143.245.181|:80... connected.
HTTP request sent, awaiting response... 200 OK
Length: 8399 (8.2K) [application/octet-stream]
Saving to: ‘rCRSd.fa.gz’
rCRSd.fa.gz 100%[===================>] 8.20K --.-KB/s in 0.006s
2021-03-09 12:22:40 (1.35 MB/s) - ‘rCRSd.fa.gz’ saved [8399/8399]
!refgenie build rCRSd/fasta -c refgenie.yaml --files fasta=rCRSd.fa.gz -R
Using 'default' as the default tag for 'rCRSd/fasta'
Recipe validated successfully against a schema: /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/refgenie/schemas/recipe_schema.yaml
Building 'rCRSd/fasta:default' using 'fasta' recipe
Initializing genome: rCRSd
Loaded AnnotatedSequenceDigestList (1 sequences)
Set genome alias (94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4: rCRSd)
Created alias directories:
- /Users/mstolarczyk/code/refgenie/docs_jupyter/alias/rCRSd
Saving outputs to:
- content: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4
- logs: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/_refgenie_build
### Pipeline run code and environment:
* Command: `/Library/Frameworks/Python.framework/Versions/3.6/bin/refgenie build rCRSd/fasta -c refgenie.yaml --files fasta=rCRSd.fa.gz -R`
* Compute host: MichalsMBP
* Working dir: /Users/mstolarczyk/code/refgenie/docs_jupyter
* Outfolder: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/_refgenie_build/
* Pipeline started at: (03-09 12:22:41) elapsed: 0.0 _TIME_
### Version log:
* Python version: 3.6.5
* Pypiper dir: `/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pypiper`
* Pypiper version: 0.12.1
* Pipeline dir: `/Library/Frameworks/Python.framework/Versions/3.6/bin`
* Pipeline version: None
### Arguments passed to pipeline:
* `asset_registry_paths`: `['rCRSd/fasta']`
* `assets`: `None`
* `command`: `build`
* `config_file`: `refgenie.yaml`
* `docker`: `False`
* `files`: `[['fasta=rCRSd.fa.gz']]`
* `genome`: `None`
* `genome_config`: `refgenie.yaml`
* `genome_description`: `None`
* `logdev`: `False`
* `new_start`: `False`
* `outfolder`: `/Users/mstolarczyk/code/refgenie/docs_jupyter/data`
* `params`: `None`
* `recipe`: `None`
* `recover`: `True`
* `requirements`: `False`
* `silent`: `False`
* `skip_read_lock`: `False`
* `tag_description`: `None`
* `verbosity`: `None`
* `volumes`: `None`
----------------------------------------
Target to produce: `/Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/_refgenie_build/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4_fasta__default.flag`
> `cp rCRSd.fa.gz /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa.gz` (63575)
<pre>
psutil.ZombieProcess process still exists but it's a zombie (pid=63575)
Warning: couldn't add memory use for process: 63575
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0GB.
PID: 63575; Command: cp; Return code: 0; Memory used: 0GB
> `gzip -df /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa.gz` (63576)
<pre>
psutil.ZombieProcess process still exists but it's a zombie (pid=63576)
Warning: couldn't add memory use for process: 63576
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0GB.
PID: 63576; Command: gzip; Return code: 0; Memory used: 0GB
> `samtools faidx /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa` (63577)
<pre>
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0.001GB.
PID: 63577; Command: samtools; Return code: 0; Memory used: 0.001GB
> `cut -f 1,2 /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa.fai > /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.chrom.sizes` (63578)
<pre>
psutil.ZombieProcess process still exists but it's a zombie (pid=63578)
Warning: couldn't add memory use for process: 63578
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0.001GB.
PID: 63578; Command: cut; Return code: 0; Memory used: 0GB
> `touch /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/_refgenie_build/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4_fasta__default.flag` (63580)
<pre>
psutil.ZombieProcess process still exists but it's a zombie (pid=63580)
Warning: couldn't add memory use for process: 63580
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0.001GB.
PID: 63580; Command: touch; Return code: 0; Memory used: 0GB
Asset digest: 4eb430296bc02ed7e4006624f1d5ac53
Default tag for '94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta' set to: default
### Pipeline completed. Epilogue
* Elapsed time (this run): 0:00:00
* Total elapsed time (all runs): 0:00:00
* Peak memory (this run): 0.0015 GB
* Pipeline completed time: 2021-03-09 12:22:41
Finished building 'fasta' asset
Created alias directories:
- /Users/mstolarczyk/code/refgenie/docs_jupyter/alias/rCRSd/fasta/default
The asset should be available for local use, let's call refgenie list to check it:
!refgenie list -c refgenie.yaml --genome rCRSd
Local refgenie assets
Server subscriptions: http://rg.databio.org
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┓
┃ genome ┃ asset (seek_keys) ┃ tags ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━┩
│ rCRSd │ fasta (fasta, fai, chrom_sizes) │ default │
└───────────┴────────────────────────────────────────────┴───────────┘
We can retrieve the path to this asset with:
!refgenie seek rCRSd/fasta -c refgenie.yaml
/Users/mstolarczyk/code/refgenie/docs_jupyter/alias/rCRSd/fasta/default/rCRSd.fa
Naturally, we can do the same thing from within Python:
rgc = refgenconf.RefGenConf("refgenie.yaml")
rgc.seek("rCRSd", "fasta")
'/Users/mstolarczyk/code/refgenie/docs_jupyter/alias/rCRSd/fasta/default/rCRSd.fa'
Now, if we have bowtie2-build in our $PATH we can build the bowtie2_index asset with no further requirements.
Let's check the requirements with refgenie build --requirements:
!refgenie build rCRSd/bowtie2_index -c refgenie.yaml --requirements
'bowtie2_index' recipe requirements:
- assets:
fasta (fasta asset for genome); default: fasta
Since I already have the fasta asset, that means I don't need anything else to build the bowtie2_index.
!refgenie build rCRSd/bowtie2_index -c refgenie.yaml
Using 'default' as the default tag for 'rCRSd/bowtie2_index'
Recipe validated successfully against a schema: /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/refgenie/schemas/recipe_schema.yaml
Building 'rCRSd/bowtie2_index:default' using 'bowtie2_index' recipe
Saving outputs to:
- content: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4
- logs: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/_refgenie_build
### Pipeline run code and environment:
* Command: `/Library/Frameworks/Python.framework/Versions/3.6/bin/refgenie build rCRSd/bowtie2_index -c refgenie.yaml`
* Compute host: MichalsMBP
* Working dir: /Users/mstolarczyk/code/refgenie/docs_jupyter
* Outfolder: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/_refgenie_build/
* Pipeline started at: (03-09 12:22:45) elapsed: 0.0 _TIME_
### Version log:
* Python version: 3.6.5
* Pypiper dir: `/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pypiper`
* Pypiper version: 0.12.1
* Pipeline dir: `/Library/Frameworks/Python.framework/Versions/3.6/bin`
* Pipeline version: None
### Arguments passed to pipeline:
* `asset_registry_paths`: `['rCRSd/bowtie2_index']`
* `assets`: `None`
* `command`: `build`
* `config_file`: `refgenie.yaml`
* `docker`: `False`
* `files`: `None`
* `genome`: `None`
* `genome_config`: `refgenie.yaml`
* `genome_description`: `None`
* `logdev`: `False`
* `new_start`: `False`
* `outfolder`: `/Users/mstolarczyk/code/refgenie/docs_jupyter/data`
* `params`: `None`
* `recipe`: `None`
* `recover`: `False`
* `requirements`: `False`
* `silent`: `False`
* `skip_read_lock`: `False`
* `tag_description`: `None`
* `verbosity`: `None`
* `volumes`: `None`
----------------------------------------
Target to produce: `/Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/_refgenie_build/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4_bowtie2_index__default.flag`
> `bowtie2-build /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4` (63609)
<pre>
Settings:
Output files: "/Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.*.bt2"
Line rate: 6 (line is 64 bytes)
Lines per side: 1 (side is 64 bytes)
Offset rate: 4 (one in 16)
FTable chars: 10
Strings: unpacked
Max bucket size: default
Max bucket size, sqrt multiplier: default
Max bucket size, len divisor: 4
Difference-cover sample period: 1024
Endianness: little
Actual local endianness: little
Sanity checking: disabled
Assertions: disabled
Random seed: 0
Sizeofs: void*:8, int:4, long:8, size_t:8
Input files DNA, FASTA:
/Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/fasta/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.fa
Building a SMALL index
Reading reference sizes
Time reading reference sizes: 00:00:00
Calculating joined length
Writing header
Reserving space for joined string
Joining reference sequences
Time to join reference sequences: 00:00:00
bmax according to bmaxDivN setting: 8284
Using parameters --bmax 6213 --dcv 1024
Doing ahead-of-time memory usage test
Passed! Constructing with these parameters: --bmax 6213 --dcv 1024
Constructing suffix-array element generator
Building DifferenceCoverSample
Building sPrime
Building sPrimeOrder
V-Sorting samples
V-Sorting samples time: 00:00:00
Allocating rank array
Ranking v-sort output
Ranking v-sort output time: 00:00:00
Invoking Larsson-Sadakane on ranks
Invoking Larsson-Sadakane on ranks time: 00:00:00
Sanity-checking and returning
Building samples
Reserving space for 12 sample suffixes
Generating random suffixes
QSorting 12 sample offsets, eliminating duplicates
QSorting sample offsets, eliminating duplicates time: 00:00:00
Multikey QSorting 12 samples
(Using difference cover)
Multikey QSorting samples time: 00:00:00
Calculating bucket sizes
Splitting and merging
Splitting and merging time: 00:00:00
Avg bucket size: 33136 (target: 6212)
Converting suffix-array elements to index image
Allocating ftab, absorbFtab
Entering Ebwt loop
Getting block 1 of 1
No samples; assembling all-inclusive block
Sorting block of length 33136 for bucket 1
(Using difference cover)
Sorting block time: 00:00:00
Returning block of 33137 for bucket 1
Exited Ebwt loop
fchr[A]: 0
fchr[C]: 10248
fchr[G]: 20610
fchr[T]: 24948
fchr[$]: 33136
Exiting Ebwt::buildToDisk()
Returning from initFromVector
Wrote 4205567 bytes to primary EBWT file: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.1.bt2
Wrote 8292 bytes to secondary EBWT file: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.2.bt2
Re-opening _in1 and _in2 as input streams
Returning from Ebwt constructor
Headers:
len: 33136
bwtLen: 33137
sz: 8284
bwtSz: 8285
lineRate: 6
offRate: 4
offMask: 0xfffffff0
ftabChars: 10
eftabLen: 20
eftabSz: 80
ftabLen: 1048577
ftabSz: 4194308
offsLen: 2072
offsSz: 8288
lineSz: 64
sideSz: 64
sideBwtSz: 48
sideBwtLen: 192
numSides: 173
numLines: 173
ebwtTotLen: 11072
ebwtTotSz: 11072
color: 0
reverse: 0
Total time for call to driver() for forward index: 00:00:00
Reading reference sizes
Time reading reference sizes: 00:00:00
Calculating joined length
Writing header
Reserving space for joined string
Joining reference sequences
Time to join reference sequences: 00:00:00
Time to reverse reference sequence: 00:00:00
bmax according to bmaxDivN setting: 8284
Using parameters --bmax 6213 --dcv 1024
Doing ahead-of-time memory usage test
Passed! Constructing with these parameters: --bmax 6213 --dcv 1024
Constructing suffix-array element generator
Building DifferenceCoverSample
Building sPrime
Building sPrimeOrder
V-Sorting samples
V-Sorting samples time: 00:00:00
Allocating rank array
Ranking v-sort output
Ranking v-sort output time: 00:00:00
Invoking Larsson-Sadakane on ranks
Invoking Larsson-Sadakane on ranks time: 00:00:00
Sanity-checking and returning
Building samples
Reserving space for 12 sample suffixes
Generating random suffixes
QSorting 12 sample offsets, eliminating duplicates
QSorting sample offsets, eliminating duplicates time: 00:00:00
Multikey QSorting 12 samples
(Using difference cover)
Multikey QSorting samples time: 00:00:00
Calculating bucket sizes
Splitting and merging
Splitting and merging time: 00:00:00
Avg bucket size: 33136 (target: 6212)
Converting suffix-array elements to index image
Allocating ftab, absorbFtab
Entering Ebwt loop
Getting block 1 of 1
No samples; assembling all-inclusive block
Sorting block of length 33136 for bucket 1
(Using difference cover)
Sorting block time: 00:00:00
Returning block of 33137 for bucket 1
Exited Ebwt loop
fchr[A]: 0
fchr[C]: 10248
fchr[G]: 20610
fchr[T]: 24948
fchr[$]: 33136
Exiting Ebwt::buildToDisk()
Returning from initFromVector
Wrote 4205567 bytes to primary EBWT file: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.rev.1.bt2
Wrote 8292 bytes to secondary EBWT file: /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4.rev.2.bt2
Re-opening _in1 and _in2 as input streams
Returning from Ebwt constructor
Headers:
len: 33136
bwtLen: 33137
sz: 8284
bwtSz: 8285
lineRate: 6
offRate: 4
offMask: 0xfffffff0
ftabChars: 10
eftabLen: 20
eftabSz: 80
ftabLen: 1048577
ftabSz: 4194308
offsLen: 2072
offsSz: 8288
lineSz: 64
sideSz: 64
sideBwtSz: 48
sideBwtLen: 192
numSides: 173
numLines: 173
ebwtTotLen: 11072
ebwtTotSz: 11072
color: 0
reverse: 1
Total time for backward call to driver() for mirror index: 00:00:00
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0.003GB.
PID: 63609; Command: bowtie2-build; Return code: 0; Memory used: 0.003GB
> `touch /Users/mstolarczyk/code/refgenie/docs_jupyter/data/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index/default/_refgenie_build/94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4_bowtie2_index__default.flag` (63611)
<pre>
psutil.ZombieProcess process still exists but it's a zombie (pid=63611)
Warning: couldn't add memory use for process: 63611
</pre>
Command completed. Elapsed time: 0:00:00. Running peak memory: 0.003GB.
PID: 63611; Command: touch; Return code: 0; Memory used: 0GB
Asset digest: 1262e30d4a87db9365d501de8559b3b4
Default tag for '94e0d21feb576e6af61cd2a798ad30682ef2428bb7eabbb4/bowtie2_index' set to: default
### Pipeline completed. Epilogue
* Elapsed time (this run): 0:00:01
* Total elapsed time (all runs): 0:00:00
* Peak memory (this run): 0.0028 GB
* Pipeline completed time: 2021-03-09 12:22:46
Finished building 'bowtie2_index' asset
Created alias directories:
- /Users/mstolarczyk/code/refgenie/docs_jupyter/alias/rCRSd/bowtie2_index/default
We can see a list of available recipes like this:
!refgenie list -c refgenie.yaml --recipes
bismark_bt1_index, bismark_bt2_index, blacklist, bowtie2_index, bwa_index, cellranger_reference, dbnsfp, dbsnp, ensembl_gtf, ensembl_rb, epilog_index, fasta, fasta_txome, feat_annotation, gencode_gtf, hisat2_index, kallisto_index, refgene_anno, salmon_index, salmon_partial_sa_index, salmon_sa_index, star_index, suffixerator_index, tallymer_index, tgMap
We can get the unique digest for any asset with refgenie id:
!refgenie id rCRSd/fasta -c refgenie.yaml
4eb430296bc02ed7e4006624f1d5ac53
Versions
from platform import python_version
python_version()
'3.6.5'
!refgenie --version
refgenie 0.10.0-dev | refgenconf 0.10.0-dev