finemap_loci failing #17
Description
1. Bug description
Hi I am unable to properly run finemap_loci with a quantitative GWAS.
Few things to highlight so far.
- The sample size column to do finemapping for a quant GWAS is not properly found even though specifying case_control = FALSE.
- Need to have a look at all of this. However, the standardised query seems wrong. Too few SNPs... I manueally filtered SNPs +-1Mb from lead variant. I had over 80K SNPs in eac loci.
- Rfast missing in MAGMA.Celltyping
2. Reproducible example
Code
columnsnames = echodata::construct_colmap(munged= FALSE,
CHR = "CHR", POS = "POS",
SNP = "SNP", P = "P",
Effect = "BETA", StdErr = "SE",
A1 = "A1", A2 = "A2",
N_cases = "N_CAS", MAF = "FREQ",
tstat = NULL, N_controls = NULL,
proportion_cases = NULL)
finemap_loci(# GENERAL ARGUMENTS
topSNPs = topSNPs,
results_dir = fullRS_path,
loci = topSNPs$Locus,
dataset_name = "LID_COX",
dataset_type = "GWAS",
force_new_subset = TRUE,
force_new_LD = FALSE,
force_new_finemap = TRUE,
remove_tmps = FALSE,
finemap_methods = c("ABF","FINEMAP","SUSIE", "POLYFUN_SUSIE"),
# Munge full sumstats first
munged = FALSE,
colmap = columnsnames,
# SUMMARY STATS ARGUMENTS
fullSS_path = newSS_name,
fullSS_genome_build = "hg19",
query_by ="tabix",
bp_distance = 10000,#500000*2,
min_MAF = 0.001,
trim_gene_limits = FALSE,
case_control = FALSE,
# FINE-MAPPING ARGUMENTS
## General
n_causal = 5,
credset_thresh = .95,
consensus_thresh = 2,
# LD ARGUMENTS
LD_reference = "1KGphase3",#"UKB",
superpopulation = "EUR",
download_method = "axel",
LD_genome_build = "hg19",
leadSNP_LD_block = FALSE,
#### PLotting args ####
plot_types = c("simple"),
show_plot = TRUE,
zoom = "1x",
tx_biotypes = NULL,
nott_epigenome = FALSE,
nott_show_placseq = FALSE,
nott_binwidth = 200,
nott_bigwig_dir = NULL,
xgr_libnames = NULL,
roadmap = FALSE,
roadmap_query = NULL,
#### General args ####
seed = 2022,
nThread = 20,
verbose = TRUE
)
Console output
PolyFun submodule already installed.
┌─────────────────────────────────────────────────┐
│ │
│ )))> 🦇 RP11-240A16.1 [locus 1 / 3] 🦇 <((( │
│ │
└─────────────────────────────────────────────────┘
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 1 ▶▶▶ Query 🔎 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+ Query Method: tabix
Constructing GRanges query using min/max ranges within a single chromosome.
query_dat is already a GRanges object. Returning directly.
========= echotabix::convert =========
Converting full summary stats file to tabix format for fast querying.
Inferred format: 'table'
Explicit format: 'table'
Inferring comment_char from tabular header: 'CHR'
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 ^'CHR' .../QC_V2.txt; grep
-v ^'CHR' .../QC_V2.txt | sort
-k1,1n
-k2,2n ) > .../file2efc11009c2a_sorted.tsv
Constructing outputs
Using existing bgzipped file: /home/rstudio/echolocatoR/echolocatoR_LID/QC_V2.txt.bgz
Set force_new=TRUE to override this.
Tabix-indexing file using: Rsamtools
Data successfully converted to bgzip-compressed, tabix-indexed format.
========= 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: 4:32425284-32445284
Adding 'query' column to results.
Retrieved data with 76 rows
Saving query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/RP11-240A16.1/RP11-240A16.1_LID_COX_subset.tsv.gz
+ Query: 76 SNPs x 10 columns.
Standardizing summary statistics subset.
Standardizing main column names.
++ Preparing A1,A1 cols
++ Preparing MAF,Freq cols.
++ Could not infer MAF.
++ Preparing N_cases,N_controls cols.
++ Preparing proportion_cases col.
++ proportion_cases not included in data subset.
Preparing sample size column (N).
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
+ Imputing t-statistic from Effect and StdErr.
+ leadSNP missing. Assigning new one by min p-value.
++ Ensuring Effect,StdErr,P are numeric.
++ Ensuring 1 SNP per row and per genomic coordinate.
++ Removing extra whitespace
+ Standardized query: 76 SNPs x 12 columns.
++ Saving standardized query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/RP11-240A16.1/RP11-240A16.1_LID_COX_subset.tsv.gz
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 2 ▶▶▶ Extract Linkage Disequilibrium 🔗 ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
LD_reference identified as: 1kg.
Previously computed LD_matrix detected. Importing: /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/RP11-240A16.1/LD/RP11-240A16.1.1KGphase3_LD.RDS
LD_reference identified as: r.
Converting obj to sparseMatrix.
+ FILTER:: Filtering by LD features.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 3 ▶▶▶ Filter SNPs 🚰 ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 76 x 12
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 76 SNPs.
+ dat = 76 SNPs.
+ 76 SNPs in common.
Converting obj to sparseMatrix.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 4 ▶▶▶ Fine-map 🔊 ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Gathering method sources.
Gathering method citations.
Preparing sample size column (N).
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
Gathering method sources.
Gathering method citations.
Gathering method sources.
Gathering method citations.
ABF
🚫 Missing required column(s) for ABF [skipping]: N, MAF, proportion_cases
FINEMAP
✅ All required columns present.
⚠ Missing optional column(s) for FINEMAP: MAF, N
SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for SUSIE: N
POLYFUN_SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for POLYFUN_SUSIE: MAF, N
++ Fine-mapping using 3 tool(s): FINEMAP, SUSIE, POLYFUN_SUSIE
+++ Multi-finemap:: FINEMAP +++
Preparing sample size column (N).
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
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 76 SNPs.
+ dat = 76 SNPs.
+ 76 SNPs in common.
Converting obj to sparseMatrix.
Constructing master file.
Optional MAF col missing. Replacing with all '.1's
Constructing data.z file.
Constructing data.ld file.
FINEMAP path: /home/rstudio/.cache/R/echofinemap/FINEMAP/finemap_v1.4.1_x86_64/finemap_v1.4.1_x86_64
Inferred FINEMAP version: 1.4.1
Running FINEMAP.
cd .../RP11-240A16.1 &&
.../finemap_v1.4.1_x86_64
--sss
--in-files .../master
--log
--n-threads 20
--n-causal-snps 5
Error : Master file '/home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/RP11-240A16.1/FINEMAP/master' is missing an entry in line 2 column 'n_samples'!
|--------------------------------------|
| Welcome to FINEMAP v1.4.1 |
| |
| (c) 2015-2022 University of Helsinki |
| |
| Help : |
| - ./finemap --help |
| - www.finemap.me |
| - www.christianbenner.com |
| |
| Contact : |
| - finemap@christianbenner.com |
| - matti.pirinen@helsinki.fi |
|--------------------------------------|
--------
SETTINGS
--------
- dataset : all
- corr-config : 0.95
- n-causal-snps : 5
- n-configs-top : 50000
- n-conv-sss : 100
- n-iter : 100000
- n-threads : 20
- prior-k0 : 0
- prior-std : 0.05
- prob-conv-sss-tol : 0.001
- prob-cred-set : 0.95
+++ Multi-finemap:: SUSIE +++
Loading required namespace: Rfast
Failed with error: 'there is no package called 'Rfast''
Preparing sample size column (N).
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
sample_size=NULL: must be valid integer.Locus RP11-240A16.1 complete in: 0.26 min
┌─────────────────────────────────────────┐
│ │
│ )))> 🦇 XYLT1 [locus 2 / 3] 🦇 <((( │
│ │
└─────────────────────────────────────────┘
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 1 ▶▶▶ Query 🔎 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+ Query Method: tabix
Constructing GRanges query using min/max ranges within a single chromosome.
query_dat is already a GRanges object. Returning directly.
========= echotabix::convert =========
Converting full summary stats file to tabix format for fast querying.
Inferred format: 'table'
Explicit format: 'table'
Inferring comment_char from tabular header: 'CHR'
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 ^'CHR' .../QC_V2.txt; grep
-v ^'CHR' .../QC_V2.txt | sort
-k1,1n
-k2,2n ) > .../file2efc3ee606a8_sorted.tsv
Constructing outputs
Using existing bgzipped file: /home/rstudio/echolocatoR/echolocatoR_LID/QC_V2.txt.bgz
Set force_new=TRUE to override this.
Tabix-indexing file using: Rsamtools
Data successfully converted to bgzip-compressed, tabix-indexed format.
========= 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: 16:17034975-17054975
Adding 'query' column to results.
Retrieved data with 82 rows
Saving query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/XYLT1/XYLT1_LID_COX_subset.tsv.gz
+ Query: 82 SNPs x 10 columns.
Standardizing summary statistics subset.
Standardizing main column names.
++ Preparing A1,A1 cols
++ Preparing MAF,Freq cols.
++ Could not infer MAF.
++ Preparing N_cases,N_controls cols.
++ Preparing proportion_cases col.
++ proportion_cases not included in data subset.
Preparing sample size column (N).
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
+ Imputing t-statistic from Effect and StdErr.
+ leadSNP missing. Assigning new one by min p-value.
++ Ensuring Effect,StdErr,P are numeric.
++ Ensuring 1 SNP per row and per genomic coordinate.
++ Removing extra whitespace
+ Standardized query: 80 SNPs x 12 columns.
++ Saving standardized query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/XYLT1/XYLT1_LID_COX_subset.tsv.gz
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 2 ▶▶▶ Extract Linkage Disequilibrium 🔗 ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
LD_reference identified as: 1kg.
Previously computed LD_matrix detected. Importing: /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/XYLT1/LD/XYLT1.1KGphase3_LD.RDS
LD_reference identified as: r.
Converting obj to sparseMatrix.
+ FILTER:: Filtering by LD features.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 3 ▶▶▶ Filter SNPs 🚰 ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 79 x 12
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 79 SNPs.
+ dat = 79 SNPs.
+ 79 SNPs in common.
Converting obj to sparseMatrix.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 4 ▶▶▶ Fine-map 🔊 ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Gathering method sources.
Gathering method citations.
Preparing sample size column (N).
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
Gathering method sources.
Gathering method citations.
Gathering method sources.
Gathering method citations.
ABF
🚫 Missing required column(s) for ABF [skipping]: N, MAF, proportion_cases
FINEMAP
✅ All required columns present.
⚠ Missing optional column(s) for FINEMAP: MAF, N
SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for SUSIE: N
POLYFUN_SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for POLYFUN_SUSIE: MAF, N
++ Fine-mapping using 3 tool(s): FINEMAP, SUSIE, POLYFUN_SUSIE
+++ Multi-finemap:: FINEMAP +++
Preparing sample size column (N).
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
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 79 SNPs.
+ dat = 79 SNPs.
+ 79 SNPs in common.
Converting obj to sparseMatrix.
Constructing master file.
Optional MAF col missing. Replacing with all '.1's
Constructing data.z file.
Constructing data.ld file.
FINEMAP path: /home/rstudio/.cache/R/echofinemap/FINEMAP/finemap_v1.4.1_x86_64/finemap_v1.4.1_x86_64
Inferred FINEMAP version: 1.4.1
Running FINEMAP.
cd .../XYLT1 &&
.../finemap_v1.4.1_x86_64
--sss
--in-files .../master
--log
--n-threads 20
--n-causal-snps 5
Error : Master file '/home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/XYLT1/FINEMAP/master' is missing an entry in line 2 column 'n_samples'!
|--------------------------------------|
| Welcome to FINEMAP v1.4.1 |
| |
| (c) 2015-2022 University of Helsinki |
| |
| Help : |
| - ./finemap --help |
| - www.finemap.me |
| - www.christianbenner.com |
| |
| Contact : |
| - finemap@christianbenner.com |
| - matti.pirinen@helsinki.fi |
|--------------------------------------|
--------
SETTINGS
--------
- dataset : all
- corr-config : 0.95
- n-causal-snps : 5
- n-configs-top : 50000
- n-conv-sss : 100
- n-iter : 100000
- n-threads : 20
- prior-k0 : 0
- prior-std : 0.05
- prob-conv-sss-tol : 0.001
- prob-cred-set : 0.95
+++ Multi-finemap:: SUSIE +++
Loading required namespace: Rfast
Failed with error: 'there is no package called 'Rfast''
In addition: Warning message:
In SUSIE(dat = dat, dataset_type = dataset_type, LD_matrix = LD_matrix, :
Install Rfast to speed up susieR even further:
install.packages('Rfast')
Preparing sample size column (N).
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
sample_size=NULL: must be valid integer.Locus XYLT1 complete in: 0.3 min
┌────────────────────────────────────────┐
│ │
│ )))> 🦇 LRP8 [locus 3 / 3] 🦇 <((( │
│ │
└────────────────────────────────────────┘
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 1 ▶▶▶ Query 🔎 ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+ Query Method: tabix
Constructing GRanges query using min/max ranges within a single chromosome.
query_dat is already a GRanges object. Returning directly.
========= echotabix::convert =========
Converting full summary stats file to tabix format for fast querying.
Inferred format: 'table'
Explicit format: 'table'
Inferring comment_char from tabular header: 'CHR'
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 ^'CHR' .../QC_V2.txt; grep
-v ^'CHR' .../QC_V2.txt | sort
-k1,1n
-k2,2n ) > .../file2efc33368771_sorted.tsv
Constructing outputs
Using existing bgzipped file: /home/rstudio/echolocatoR/echolocatoR_LID/QC_V2.txt.bgz
Set force_new=TRUE to override this.
Tabix-indexing file using: Rsamtools
Data successfully converted to bgzip-compressed, tabix-indexed format.
========= 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: 1:53768300-53788300
Adding 'query' column to results.
Retrieved data with 52 rows
Saving query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/LRP8/LRP8_LID_COX_subset.tsv.gz
+ Query: 52 SNPs x 10 columns.
Standardizing summary statistics subset.
Standardizing main column names.
++ Preparing A1,A1 cols
++ Preparing MAF,Freq cols.
++ Could not infer MAF.
++ Preparing N_cases,N_controls cols.
++ Preparing proportion_cases col.
++ proportion_cases not included in data subset.
Preparing sample size column (N).
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
+ Imputing t-statistic from Effect and StdErr.
+ leadSNP missing. Assigning new one by min p-value.
++ Ensuring Effect,StdErr,P are numeric.
++ Ensuring 1 SNP per row and per genomic coordinate.
++ Removing extra whitespace
+ Standardized query: 52 SNPs x 12 columns.
++ Saving standardized query ==> /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/LRP8/LRP8_LID_COX_subset.tsv.gz
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 2 ▶▶▶ Extract Linkage Disequilibrium 🔗 ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
LD_reference identified as: 1kg.
Previously computed LD_matrix detected. Importing: /home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/LRP8/LD/LRP8.1KGphase3_LD.RDS
LD_reference identified as: r.
Converting obj to sparseMatrix.
+ FILTER:: Filtering by LD features.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 3 ▶▶▶ Filter SNPs 🚰 ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 51 x 12
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 51 SNPs.
+ dat = 51 SNPs.
+ 51 SNPs in common.
Converting obj to sparseMatrix.
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 4 ▶▶▶ Fine-map 🔊 ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Gathering method sources.
Gathering method citations.
Preparing sample size column (N).
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
Gathering method sources.
Gathering method citations.
Gathering method sources.
Gathering method citations.
ABF
🚫 Missing required column(s) for ABF [skipping]: N, MAF, proportion_cases
FINEMAP
✅ All required columns present.
⚠ Missing optional column(s) for FINEMAP: MAF, N
SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for SUSIE: N
POLYFUN_SUSIE
✅ All required columns present.
⚠ Missing optional column(s) for POLYFUN_SUSIE: MAF, N
++ Fine-mapping using 3 tool(s): FINEMAP, SUSIE, POLYFUN_SUSIE
+++ Multi-finemap:: FINEMAP +++
Preparing sample size column (N).
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
+ Subsetting LD matrix and dat to common SNPs...
Removing unnamed rows/cols
Replacing NAs with 0
+ LD_matrix = 51 SNPs.
+ dat = 51 SNPs.
+ 51 SNPs in common.
Converting obj to sparseMatrix.
Constructing master file.
Optional MAF col missing. Replacing with all '.1's
Constructing data.z file.
Constructing data.ld file.
FINEMAP path: /home/rstudio/.cache/R/echofinemap/FINEMAP/finemap_v1.4.1_x86_64/finemap_v1.4.1_x86_64
Inferred FINEMAP version: 1.4.1
Running FINEMAP.
cd .../LRP8 &&
.../finemap_v1.4.1_x86_64
--sss
--in-files .../master
--log
--n-threads 20
--n-causal-snps 5
Error : Master file '/home/rstudio/echolocatoR/echolocatoR_LID/RESULTS/GWAS/LID_COX/LRP8/FINEMAP/master' is missing an entry in line 2 column 'n_samples'!
|--------------------------------------|
| Welcome to FINEMAP v1.4.1 |
| |
| (c) 2015-2022 University of Helsinki |
| |
| Help : |
| - ./finemap --help |
| - www.finemap.me |
| - www.christianbenner.com |
| |
| Contact : |
| - finemap@christianbenner.com |
| - matti.pirinen@helsinki.fi |
|--------------------------------------|
--------
SETTINGS
--------
- dataset : all
- corr-config : 0.95
- n-causal-snps : 5
- n-configs-top : 50000
- n-conv-sss : 100
- n-iter : 100000
- n-threads : 20
- prior-k0 : 0
- prior-std : 0.05
- prob-conv-sss-tol : 0.001
- prob-cred-set : 0.95
+++ Multi-finemap:: SUSIE +++
Loading required namespace: Rfast
Failed with error: 'there is no package called 'Rfast''
In addition: Warning message:
In SUSIE(dat = dat, dataset_type = dataset_type, LD_matrix = LD_matrix, :
Install Rfast to speed up susieR even further:
install.packages('Rfast')
Preparing sample size column (N).
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
sample_size=NULL: must be valid integer.Locus LRP8 complete in: 0.26 min
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Step 6 ▶▶▶ Postprocess data 🎁 ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
Returning results as nested list.
All loci done in: 0.81 min
$`RP11-240A16.1`
NULL
$XYLT1
NULL
$LRP8
NULL
$merged_dat
Null data.table (0 rows and 0 cols)
Warning message:
In SUSIE(dat = dat, dataset_type = dataset_type, LD_matrix = LD_matrix, :
Install Rfast to speed up susieR even further:
install.packages('Rfast')
Data
> head(data_2)
CHR BP SNP A1 A2 FREQ BETA SE P N_CAS
1: 1 731718 rs58276399 t c 0.8837 -0.1775 0.1583 0.2621 1297
2: 1 731718 rs142557973 t c 0.8837 -0.1775 0.1583 0.2621 1297
3: 1 734349 rs141242758 t c 0.8843 -0.1577 0.1593 0.3223 1297
4: 1 753541 rs2073813 a g 0.1257 0.0721 0.1177 0.5399 2687
5: 1 766007 rs61768174 a c 0.9005 -0.2559 0.1642 0.1190 1297
6: 1 769223 rs60320384 c g 0.8749 -0.0772 0.1178 0.5124 2687
> head(topSNPs)
# A tibble: 3 × 7
Locus Gene CHR POS SNP P BETA
<chr> <chr> <fct> <int> <chr> <dbl> <dbl>
1 RP11-240A16.1 RP11-240A16.1 4 32435284 rs189093213 0.00000000167 1.12
2 XYLT1 XYLT1 16 17044975 rs180924818 0.00000000626 -1.14
3 LRP8 LRP8 1 53778300 rs72673189 0.0000000153 1.02
3. Session info
Details
> sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] SNPlocs.Hsapiens.dbSNP144.GRCh37_0.99.20 BSgenome_1.65.2 rtracklayer_1.57.0
[4] Biostrings_2.65.3 XVector_0.37.1 GenomicRanges_1.49.1
[7] GenomeInfoDb_1.33.5 IRanges_2.31.2 S4Vectors_0.35.3
[10] BiocGenerics_0.43.1 forcats_0.5.2 stringr_1.4.1
[13] dplyr_1.0.10 purrr_0.3.4 readr_2.1.2
[16] tidyr_1.2.0 tibble_3.1.8 ggplot2_3.3.6
[19] tidyverse_1.3.2 data.table_1.14.2 echolocatoR_2.0.1
loaded via a namespace (and not attached):
[1] Hmisc_4.7-1 class_7.3-20 ps_1.7.1
[4] Rsamtools_2.13.4 rprojroot_2.0.3 echotabix_0.99.8
[7] crayon_1.5.1 MASS_7.3-58.1 nlme_3.1-159
[10] backports_1.4.1 reprex_2.0.2 basilisk_1.9.2
[13] rlang_1.0.5 readxl_1.4.1 irlba_2.3.5
[16] nloptr_2.0.3 callr_3.7.2 limma_3.53.6
[19] filelock_1.0.2 proto_1.0.0 BiocParallel_1.31.12
[22] rjson_0.2.21 bit64_4.0.5 glue_1.6.2
[25] mixsqp_0.3-43 parallel_4.2.0 processx_3.7.0
[28] AnnotationDbi_1.59.1 HGNChelper_0.8.1 haven_2.5.1
[31] tidyselect_1.1.2 SummarizedExperiment_1.27.2 coloc_5.1.0
[34] usethis_2.1.6 XML_3.99-0.10 ggpubr_0.4.0
[37] GenomicAlignments_1.33.1 catalogueR_1.0.0 echoplot_0.99.5
[40] chron_2.3-57 xtable_1.8-4 ggnetwork_0.5.10
[43] magrittr_2.0.3 evaluate_0.16 cli_3.3.0
[46] zlibbioc_1.43.0 rstudioapi_0.14 miniUI_0.1.1.1
[49] rpart_4.1.16 echoannot_0.99.7 ensembldb_2.21.4
[52] treeio_1.21.2 shiny_1.7.2 xfun_0.32
[55] BSgenome.Hsapiens.1000genomes.hs37d5_0.99.1 pkgbuild_1.3.1 cluster_2.1.3
[58] echoconda_0.99.7 KEGGREST_1.37.3 interactiveDisplayBase_1.35.0
[61] expm_0.999-6 ggrepel_0.9.1 SNPlocs.Hsapiens.dbSNP155.GRCh37_0.99.22
[64] biovizBase_1.45.0 ape_5.6-2 echodata_0.99.12
[67] png_0.1-7 reshape_0.8.9 withr_2.5.0
[70] bitops_1.0-7 RBGL_1.73.0 plyr_1.8.7
[73] cellranger_1.1.0 AnnotationFilter_1.21.0 e1071_1.7-11
[76] pillar_1.8.1 cachem_1.0.6 GenomicFeatures_1.49.6
[79] fs_1.5.2 googleAuthR_2.0.0 echoLD_0.99.7
[82] osfr_0.2.8 snpStats_1.47.1 vctrs_0.4.1
[85] ellipsis_0.3.2 generics_0.1.3 gsubfn_0.7
[88] devtools_2.4.4 tools_4.2.0 foreign_0.8-82
[91] munsell_0.5.0 susieR_0.12.27 proxy_0.4-27
[94] DelayedArray_0.23.1 abind_1.4-5 fastmap_1.1.0
[97] compiler_4.2.0 pkgload_1.3.0 httpuv_1.6.5
[100] ExperimentHub_2.5.0 sessioninfo_1.2.2 ewceData_1.5.0
[103] plotly_4.10.0 DescTools_0.99.46 GenomeInfoDbData_1.2.8
[106] gridExtra_2.3 lattice_0.20-45 dir.expiry_1.5.0
[109] deldir_1.0-6 utf8_1.2.2 later_1.3.0
[112] BiocFileCache_2.5.0 jsonlite_1.8.0 GGally_2.1.2
[115] scales_1.2.1 gld_2.6.5 graph_1.75.0
[118] tidytree_0.4.0 carData_3.0-5 lazyeval_0.2.2
[121] promises_1.2.0.1 car_3.1-0 RCircos_1.2.2
[124] latticeExtra_0.6-30 R.utils_2.12.0 reticulate_1.26
[127] checkmate_2.1.0 rmarkdown_2.16 openxlsx_4.2.5
[130] dichromat_2.0-0.1 Biobase_2.57.1 igraph_1.3.4
[133] survival_3.3-1 yaml_2.3.5 htmltools_0.5.3
[136] memoise_2.0.1 VariantAnnotation_1.43.3 profvis_0.3.7
[139] BiocIO_1.7.1 supraHex_1.35.0 viridisLite_0.4.1
[142] digest_0.6.29 assertthat_0.2.1 mime_0.12
[145] piggyback_0.1.3 rappdirs_0.3.3 dnet_1.1.7
[148] downloadR_0.99.4 RSQLite_2.2.16 sqldf_0.4-11
[151] yulab.utils_0.0.5 Exact_3.1 remotes_2.4.2
[154] orthogene_1.3.2 urlchecker_1.0.1 blob_1.2.3
[157] R.oo_1.25.0 splines_4.2.0 Formula_1.2-4
[160] googledrive_2.0.0 AnnotationHub_3.5.0 OrganismDbi_1.39.1
[163] ProtGenerics_1.29.0 RCurl_1.98-1.8 broom_1.0.1
[166] hms_1.1.2 gprofiler2_0.2.1 modelr_0.1.9
[169] colorspace_2.0-3 base64enc_0.1-3 BiocManager_1.30.18
[172] aplot_0.1.6 echofinemap_0.99.3 nnet_7.3-17
[175] Rcpp_1.0.9 mvtnorm_1.1-3 fansi_1.0.3
[178] tzdb_0.3.0 brio_1.1.3 R6_2.5.1
[181] grid_4.2.0 crul_1.2.0 lifecycle_1.0.1
[184] rootSolve_1.8.2.3 zip_2.2.0 MungeSumstats_1.5.13
[187] ggsignif_0.6.3 curl_4.3.2 googlesheets4_1.0.1
[190] minqa_1.2.4 testthat_3.1.4 XGR_1.1.8
[193] Matrix_1.4-1 desc_1.4.1 ggbio_1.45.0
[196] RColorBrewer_1.1-3 htmlwidgets_1.5.4 biomaRt_2.53.2
[199] gridGraphics_0.5-1 MAGMA.Celltyping_2.0.7 rvest_1.0.3
[202] lmom_2.9 htmlTable_2.4.1 patchwork_1.1.2
[205] codetools_0.2-18 matrixStats_0.62.0 lubridate_1.8.0
[208] EWCE_1.5.7 prettyunits_1.1.1 SingleCellExperiment_1.19.0
[211] dbplyr_2.2.1 basilisk.utils_1.9.2 R.methodsS3_1.8.2
[214] gtable_0.3.1 DBI_1.1.3 ggfun_0.0.7
[217] httr_1.4.4 stringi_1.7.8 progress_1.2.2
[220] reshape2_1.4.4 viridis_0.6.2 hexbin_1.28.2
[223] Rgraphviz_2.41.1 ggtree_3.5.3 DT_0.24
[226] xml2_1.3.3 ggdendro_0.1.23 boot_1.3-28
[229] lme4_1.1-30 restfulr_0.0.15 RNOmni_1.0.1
[232] interp_1.1-3 ggplotify_0.1.0 homologene_1.4.68.19.3.27
[235] BiocVersion_3.16.0 bit_4.0.4 jpeg_0.1-9
[238] MatrixGenerics_1.9.1 babelgene_22.3 pkgconfig_2.0.3
[241] gargle_1.2.0 rstatix_0.7.0 knitr_1.40