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echoverse - Failing to find an unknown package #87

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AMCalejandro opened this issue Mar 30, 2022 · 7 comments
Closed

echoverse - Failing to find an unknown package #87

AMCalejandro opened this issue Mar 30, 2022 · 7 comments
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@bschilder
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bug Something isn't working

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@AMCalejandro
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AMCalejandro commented Mar 30, 2022 •
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1. Bug description

finemap_loci pipeline fails to find echoverse package?

Console output

Registered S3 method overwritten by 'GGally':
  method from   
  +.gg   ggplot2
⠊⠉⠡⣀⣀⠊⠉⠡⣀⣀⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠                                    
⠌⢁⡐⠉⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠉⢂⡈⠑⣀⠉⢄⡈⠡⣀                                    
⠌⡈⡐⢂⢁⠒⡈⡐⢂⢁⠒⡈⡐⢂⢁⠑⡈⡈⢄⢁⠡⠌⡈⠤⢁⠡⠌⡈⠤⢁⠡⠌⡈⡠⢁⢁⠊⡈⡐⢂                                    

── 🦇  🦇  🦇 e c h o l o c a t o R 🦇  🦇  🦇 ─────────────────────────────────

── v2.0.0 ──────────────────────────────────────────────────────────────────────
⠌⡈⡐⢂⢁⠒⡈⡐⢂⢁⠒⡈⡐⢂⢁⠑⡈⡈⢄⢁⠡⠌⡈⠤⢁⠡⠌⡈⠤⢁⠡⠌⡈⡠⢁⢁⠊⡈⡐⢂                                    
⠌⢁⡐⠉⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠊⢂⡐⠑⣀⠉⢂⡈⠑⣀⠉⢄⡈⠡⣀                                    
⠊⠉⠡⣀⣀⠊⠉⠡⣀⣀⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠⠊⠉⠢⣀⡠                                    
ⓞ If you use echolocatoR, please cite:                                          
     ▶ Brian M Schilder, Jack Humphrey, Towfique                                
     Raj (2021) echolocatoR: an automated                                       
     end-to-end statistical and functional                                      
     genomic fine-mapping pipeline,                                             
     Bioinformatics; btab658,                                                   
     https://doi.org/10.1093/bioinformatics/btab658                             
ⓞ Please report any bugs/feature requests on GitHub:
     ▶
     https://github.com/RajLabMSSM/echolocatoR/issues
ⓞ Contributions are welcome!:
     ▶
     https://github.com/RajLabMSSM/echolocatoR/pulls

────────────────────────────────────────────────────────────────────────────────
echoconda:: Conda already installed.
echoconda:: Active conda env: 'echoverse'
echoconda:: Requested conda_env is already active: 'echoverse'
echoconda:: Attempting to activate conda env: 'echoverse'

)   )  ) ))))))}}}}}}}} LINC00511  ( 1  /  2 ) {{{{{{{{{(((((( (  (   (
+ Extracting relevant variants from fullSS...
+ Query Method: tabix
Constructing GRanges query using min/max ranges across one or more chromosomes.
+ as_blocks=TRUE: Will query a single range per chromosome that covers all regions requested (plus anything in between).
========= echotabix::convert =========
Converting full summary stats file to tabix format for fast querying.
Inferring comment_char from header: '#MarkerName'
Determining chrom type from file header.
Chromosome format: 1
Detecting column delimiter.
Identified column separator: \t
Sorting rows by coordinates via bash.
Searching for header row with grep.
( grep ^'#MarkerName' .../for_echolocatoR_axialOutcome_3.tsv; grep
    -v ^'#MarkerName' .../for_echolocatoR_axialOutcome_3.tsv | sort
    -k2,2n
    -k3,3n ) > .../file2dbbdf43076c0a_sorted.tsv
Constructing outputs
Using existing bgzipped file: /mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/for_echolocatoR_axialOutcome_3.tsv.bgz 
Set force_new=TRUE to override this.
Tabix-indexing file using Rsamtools
Data successfully converted to bgzip-compressed, tabix-indexed format:
  - data: /mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/for_echolocatoR_axialOutcome_3.tsv.bgz 
  - index: /mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/for_echolocatoR_axialOutcome_3.tsv.bgz.tbi
========= echotabix::query =========
query_dat is already a GRanges object. Returning directly.
Inferred format: 'table'
Querying tabular tabix file using: Rsamtools.
Checking query chromosome style is correct.
Chromosome format: 1
Retrieving data.
Converting query results to data.table.
Processing query: 17:70330179-70330179
Adding 'query' column to results.
Retrieved data with 1 rows
Saving query ==> /mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/RESULTS_25.3.2022/mixedmodels_GWAS/earlymotorPD_axial/LINC00511/LINC00511_earlymotorPD_axial_subset.tsv.gz
LD:: Standardizing summary statistics subset.
++ Preparing Gene col
Could not recognize genome build of:
 - target_genome
These will be inferred from the data.
++ Preparing A1,A1 cols
++ Preparing MAF,Freq cols
++ Inferring MAF from frequency column...
++ Preparing N_cases,N_controls cols
++ Preparing `proportion_cases` col
++ 'proportion_cases' not included in data subset.
++ Preparing N col
--
WARNING: Neff column could not be calculated as the columns N_CAS & N_CON were not found in the datset
--
+ Mapping colnames from MungeSumstats ==> echolocatoR
++ Preparing t-stat col
+ Calculating t-statistic from Effect and StdErr...
++ Assigning lead SNP
++ Ensuring Effect, StdErr, P are numeric
++ Ensuring 1 SNP per row
++ Removing extra whitespace
++ Saving subset ==> /mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/RESULTS_25.3.2022/mixedmodels_GWAS/earlymotorPD_axial/LINC00511/LINC00511_earlymotorPD_axial_subset.tsv.gz
+ Extraction completed in 42.87 seconds
+ 1 SNPs x  12 columns
+ Mapping colnames from MungeSumstats ==> echolocatoR
Standardising column headers.
First line of summary statistics file: 
CHR	POS	SNP	P	Effect	StdErr	A1	A2	Freq	MAF	t_stat	leadSNP	
Using UK Biobank LD reference panel.
+ UKB LD file name: chr17_70000001_73000001
Downloading full .gz/.npz UKB files and saving to disk.
Downloading with axel (using 95 cores).
+ Overwriting pre-existing file.
Searching for 1 package(s) across 1 conda environment(s):
 - echoverse
Identified paths for 1 / 1 packages.
1 unique package(s) found across 1 conda environment(s).
sh: 1: echoverse: not found
axel download failed. Trying with download.file.
Downloading with download.file.
Time difference of 9.8 secs
Downloading with axel (using 95 cores).
+ Overwriting pre-existing file.
Searching for 1 package(s) across 1 conda environment(s):
 - echoverse
Identified paths for 1 / 1 packages.
1 unique package(s) found across 1 conda environment(s).
sh: 1: echoverse: not found
axel download failed. Trying with download.file.
Downloading with download.file.
Time difference of 28.3 secs
Error in py_run_file_impl(file, local, convert) : 
  Unable to open file '' (does it exist?)
In addition: Warning messages:
1: 'genome' not found: hg37 
2: In system(cmd) : error in running command
3: In system(cmd) : error in running command
Fine-mapping complete in:
Time difference of 1.5 mins

Code

library(data.table)
library(echolocatoR)  
#library(tidyverse)

fullSS_path <- "/mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/for_echolocatoR_axialOutcome_3.tsv"                                                                    
fullRS_path <- "/mnt/rreal/RDS/RDS/acarrasco/ANALYSES_WORKSPACE/EARLY_PD/POST_GWAS/ECHOLOCATOR/RESULTS_25.3.2022"

top_SNPs = fread("../topSNPs_axialMotorSymptom.txt") 
top_SNPs = top_SNPs[c(5,6), ]

res = finemap_loci(top_SNPs = top_SNPs,
                                              loci = top_SNPs$Locus, 
                                              dataset_name = "earlymotorPD_axial", 
                                              dataset_type = "mixedmodels_GWAS",   
                                              force_new_subset = T, 
                                              force_new_LD = T, 
                                              force_new_finemap = T, 
                                              remove_tmps = F, 
                                               
                     # SUMMARY STATS ARGUMENTS 
                     fullSS_genome_build = "hg19",
                     fullSS_path = fullSS_path,
                     results_dir = fullRS_path,
                     query_by = "tabix", 
                     chrom_col = "CHR", position_col = "POS", snp_col = "#MarkerName", 
                     pval_col = "Pval", effect_col = "Effect", stderr_col = "StdErr", 
                     freq_col = "medianFreq", MAF_col = "calculate", 
                     A1_col = "Allele1", 
                     A2_col = "Allele2", 
                     #N_cases_col = "TotalSampleSize",
                     #N_controls = 0,
                     
                     # FILTERING ARGUMENTS 
                     ## It's often desirable to use a larger window size  
                     ## (e.g. 2Mb which is bp_distance=500000*2),  
                     ## but we use a small window here to speed up the process.  
                     bp_distance = 500000*2, 
                     min_MAF = 0.001,   
                     trim_gene_limits = F, 
                     
                     # FINE-MAPPING ARGUMENTS 
                     ## General 
                     finemap_methods = c("ABF", "SUSIE", "POLYFUN_SUSIE", "FINEMAP"),  
                     n_causal = 5, 
                     PP_threshold = .95,  
                     consensus_threshold = 2,
                     # LD ARGUMENTS  
                     LD_genome_build = "hg19",
                     LD_reference = "UKB", 
                     superpopulation = "EUR", 
                     download_method = "axel", 
                      
                     # Additional arguments - My arguments
                     case_control = F,
                     nThread = 15,
                     sample_size = 3572,
                     
                     # PLOT ARGUMENTS  
                     ## general    
                     plot_types = c("fancy"), 
                     ## Generate multiple plots of different window sizes;  
                     ### all SNPs, 4x zoomed-in, and a 50000bp window 
                     zoom = c("all","4x","10x", "30x"), 
                     ## XGR 
                     # plot.XGR_libnames=c("ENCODE_TFBS_ClusteredV3_CellTypes"),  
                     ## Roadmap 
                     roadmap=FALSE,
                     roadmap_query=NULL,
                     
                     #plot.Roadmap = F, 
                     #plot.Roadmap_query = NULL, 
                     # Nott et al. (2019) 
                     nott_epigenome=TRUE,
                     nott_show_placseq=TRUE,
                     #plot.Nott_epigenome = T,  
                     #plot.Nott_show_placseq = T,  
                     
                     verbose = TRUE,
                     
                     # ENVIRONMENT ARGS
                     conda_env= "echoverse"
                    )

2. Session info

R version 4.1.2 (2021-11-01)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS

Matrix products: default
BLAS/LAPACK: /home/acarrasco/.conda/envs/echoverse/lib/libopenblasp-r0.3.18.so

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] echolocatoR_2.0.0 data.table_1.14.2

loaded via a namespace (and not attached):
  [1] utf8_1.2.2                  reticulate_1.24            
  [3] R.utils_2.11.0              tidyselect_1.1.2           
  [5] RSQLite_2.2.11              AnnotationDbi_1.56.2       
  [7] htmlwidgets_1.5.4           grid_4.1.2                 
  [9] BiocParallel_1.28.3         XGR_1.1.7                  
 [11] munsell_0.5.0               DT_0.22                    
 [13] colorspace_2.0-3            Biobase_2.54.0             
 [15] filelock_1.0.2              OrganismDbi_1.36.0         
 [17] knitr_1.38                  supraHex_1.32.0            
 [19] rstudioapi_0.13             stats4_4.1.2               
 [21] DescTools_0.99.44           MatrixGenerics_1.6.0       
 [23] GenomeInfoDbData_1.2.7      mixsqp_0.3-43              
 [25] bit64_4.0.5                 echoconda_0.99.5           
 [27] rprojroot_2.0.2             vctrs_0.3.8                
 [29] generics_0.1.2              xfun_0.30                  
 [31] biovizBase_1.42.0           BiocFileCache_2.2.1        
 [33] R6_2.5.1                    GenomeInfoDb_1.30.1        
 [35] AnnotationFilter_1.18.0     bitops_1.0-7               
 [37] cachem_1.0.6                reshape_0.8.8              
 [39] DelayedArray_0.20.0         assertthat_0.2.1           
 [41] BiocIO_1.4.0                scales_1.1.1               
 [43] nnet_7.3-17                 rootSolve_1.8.2.3          
 [45] gtable_0.3.0                lmom_2.8                   
 [47] ggbio_1.42.0                ensembldb_2.18.4           
 [49] rlang_1.0.2                 clisymbols_1.2.0           
 [51] MungeSumstats_1.3.16        echodata_0.99.7            
 [53] splines_4.1.2               rtracklayer_1.54.0         
 [55] lazyeval_0.2.2              gargle_1.2.0               
 [57] dichromat_2.0-0             hexbin_1.28.2              
 [59] checkmate_2.0.0             BiocManager_1.30.16        
 [61] yaml_2.3.5                  reshape2_1.4.4             
 [63] snpStats_1.44.0             GenomicFeatures_1.46.5     
 [65] ggnetwork_0.5.10            backports_1.4.1            
 [67] Hmisc_4.6-0                 RBGL_1.70.0                
 [69] tools_4.1.2                 echoplot_0.99.2            
 [71] ggplot2_3.3.5               ellipsis_0.3.2             
 [73] RColorBrewer_1.1-2          proxy_0.4-26               
 [75] BiocGenerics_0.40.0         coloc_5.1.2                
 [77] Rcpp_1.0.8.3                plyr_1.8.7                 
 [79] base64enc_0.1-3             progress_1.2.2             
 [81] zlibbioc_1.40.0             purrr_0.3.4                
 [83] RCurl_1.98-1.6              prettyunits_1.1.1          
 [85] rpart_4.1.16                viridis_0.6.2              
 [87] S4Vectors_0.32.4            SummarizedExperiment_1.24.0
 [89] ggrepel_0.9.1               cluster_2.1.2              
 [91] here_1.0.1                  fs_1.5.2                   
 [93] magrittr_2.0.2              echotabix_0.99.5           
 [95] dnet_1.1.7                  openxlsx_4.2.5             
 [97] gh_1.3.0                    mvtnorm_1.1-3              
 [99] ProtGenerics_1.26.0         matrixStats_0.61.0         
[101] patchwork_1.1.1             hms_1.1.1                  
[103] XML_3.99-0.9                jpeg_0.1-9                 
[105] IRanges_2.28.0              gridExtra_2.3              
[107] compiler_4.1.2              biomaRt_2.50.3             
[109] tibble_3.1.6                crayon_1.5.1               
[111] R.oo_1.24.0                 htmltools_0.5.2            
[113] echoannot_0.99.4            tzdb_0.3.0                 
[115] Formula_1.2-4               tidyr_1.2.0                
[117] expm_0.999-6                Exact_3.1                  
[119] lubridate_1.8.0             DBI_1.1.2                  
[121] dbplyr_2.1.1                MASS_7.3-56                
[123] rappdirs_0.3.3              boot_1.3-28                
[125] Matrix_1.4-1                readr_2.1.2                
[127] piggyback_0.1.1             cli_3.2.0                  
[129] R.methodsS3_1.8.1           echofinemap_0.99.0         
[131] parallel_4.1.2              igraph_1.2.11              
[133] GenomicRanges_1.46.1        pkgconfig_2.0.3            
[135] GenomicAlignments_1.30.0    RCircos_1.2.2              
[137] foreign_0.8-82              xml2_1.3.3                 
[139] XVector_0.34.0              echoLD_0.99.1              
[141] stringr_1.4.0               VariantAnnotation_1.40.0   
[143] digest_0.6.29               graph_1.72.0               
[145] Biostrings_2.62.0           htmlTable_2.4.0            
[147] gld_2.6.4                   restfulr_0.0.13            
[149] curl_4.3.2                  Rsamtools_2.10.0           
[151] rjson_0.2.21                lifecycle_1.0.1            
[153] nlme_3.1-157                jsonlite_1.8.0             
[155] viridisLite_0.4.0           BSgenome_1.62.0            
[157] fansi_1.0.3                 downloadR_0.99.1           
[159] susieR_0.11.92              pillar_1.7.0               
[161] lattice_0.20-45             GGally_2.1.2               
[163] KEGGREST_1.34.0             fastmap_1.1.0              
[165] httr_1.4.2                  survival_3.3-1             
[167] googleAuthR_2.0.0           glue_1.6.2                 
[169] zip_2.2.0                   png_0.1-7                  
[171] bit_4.0.4                   Rgraphviz_2.38.0           
[173] class_7.3-20                stringi_1.7.6              
[175] blob_1.2.2                  latticeExtra_0.6-29        
[177] memoise_2.0.1               dplyr_1.0.8                
[179] irlba_2.3.5                 e1071_1.7-9                
[181] ape_5.6-2
@AMCalejandro AMCalejandro added the bug Something isn't working label Mar 30, 2022
@bschilder bschilder self-assigned this Aug 27, 2022
@bschilder
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Could you clarify how you created the conda environment "echoverse"?

Either way, it's odd that echoconda would be looking for a software package of the same name. Looking into this now.

@bschilder
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bschilder commented Aug 27, 2022 •
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Ok, based on the date posted i think this was a bug in an older version of echoverse. Could you try reinstalling on that branch (now master branch) and try again?

Apologies for the long delay!

@bschilder
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@AMCalejandro has this since resolved for you with the updates?

@bschilder bschilder mentioned this issue Sep 20, 2022
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@AMCalejandro
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AMCalejandro commented Sep 20, 2022 •
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Just to be clear, that conda environment was create from yml file.

Please, find it attached here


name: echoverse
channels:
  - conda-forge
  - bioconda
  - nodefaults
dependencies:
  # Python
  - python>=3.6.1
  - pandas>=0.25.0
  - pandas-plink
  - fastparquet
  - pyarrow
  - scipy
  - scikit-learn
  - tqdm
  - bitarray
  - networkx
  - rpy2
  - requests
  # Command line
  - htslib
  - plink
  - bcftools
  - wget
  - axel
  # R
  - r>=4.1.0
  - r-biocmanager
  - bioconductor-snpstats
  - bioconductor-ggbio
  - bioconductor-ensdb.hsapiens.v75
  - bioconductor-biomart
  - radian
  - pip

I am happy to reinstall echolocatoR, and give a try to run the workflow again using the default echoR_mini.
I will do so when you push the fix the sample size input to master

@bschilder
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Please, find it attached here

Perfect, thanks

I will do so when you push the fix the sample size input to master

Cool, this has already been pushed.

@AMCalejandro
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AMCalejandro commented Sep 20, 2022 via email

@bschilder
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The necessary edits were all done in echodata. So you just need to update that subpackage.

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