suppressMessages(library(tidyverse))suppressMessages(library(glue))PRE ="/Users/haekyungim/Library/CloudStorage/Box-Box/LargeFiles/imlab-data/data-Github/web-data"##PRE="/Users/margaretperry/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data "##PRE="/Users/temi/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data"## COPY THE DATE AND SLUG fields FROM THE HEADERSLUG="erap2-fine-mapping"## copy the slug from the headerbDATE='2023-03-28'## copy the date from the blog's header hereDATA =glue("{PRE}/{bDATE}-{SLUG}")if(!file.exists(DATA)) system(glue::glue("mkdir {DATA}"))WORK=DATA## move data to DATA#tempodata=("~/Downloads/tempo/gwas_catalog_v1.0.2-associations_e105_r2022-04-07.tsv")#system(glue::glue("cp {tempodata} {DATA}/"))## system(glue("open {DATA}")) ## this will open the folder
ERAP2 fine-mapping results DAPG
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## query## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_eqtl` where gene like "ENSG00000164308%"erap2 =read_csv(glue("{DATA}/bquxjob_41de6a2f_18728cf1999.csv"))
Rows: 2260 Columns: 7
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): tissue, gene, variant_id
dbl (4): rank, pip, log10_abvf, cluster_id
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
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## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_sqtl` where variant_id like "chr5_96900192%" order by pip desctauras_snp =read_csv(glue("{DATA}/bquxjob_719c0131_18728db8878.csv"))
Rows: 113 Columns: 7
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): tissue, gene_id, variant_id
dbl (4): rank, pip, log10_abvf, cluster_id
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
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## finemapping for the intron affected by chr5_96900192## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_sqtl` where gene_id like "intron_5_96900189_96901506" order by pip descintron =read_csv(glue("{DATA}/bquxjob_41bc6351_18728e4ee94.csv"))
Rows: 2439 Columns: 7
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): tissue, gene_id, variant_id
dbl (4): rank, pip, log10_abvf, cluster_id
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Warning: Groups with fewer than two data points have been dropped.
Groups with fewer than two data points have been dropped.
Groups with fewer than two data points have been dropped.
Causal SNP according to the black death paper and others is rs2248374 chr5_96900192
Source Code
---title: "ERAP2 fine-mapping"author: "Haky Im"date: "2023-03-28"categories: [analysis,how_to]format: html: code-fold: true code-summary: "Show the code"editor_options: chunk_output_type: console---```{r}suppressMessages(library(tidyverse))suppressMessages(library(glue))PRE ="/Users/haekyungim/Library/CloudStorage/Box-Box/LargeFiles/imlab-data/data-Github/web-data"##PRE="/Users/margaretperry/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data "##PRE="/Users/temi/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data"## COPY THE DATE AND SLUG fields FROM THE HEADERSLUG="erap2-fine-mapping"## copy the slug from the headerbDATE='2023-03-28'## copy the date from the blog's header hereDATA =glue("{PRE}/{bDATE}-{SLUG}")if(!file.exists(DATA)) system(glue::glue("mkdir {DATA}"))WORK=DATA## move data to DATA#tempodata=("~/Downloads/tempo/gwas_catalog_v1.0.2-associations_e105_r2022-04-07.tsv")#system(glue::glue("cp {tempodata} {DATA}/"))## system(glue("open {DATA}")) ## this will open the folder ```ERAP2 fine-mapping results DAPG```{r}## query## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_eqtl` where gene like "ENSG00000164308%"erap2 =read_csv(glue("{DATA}/bquxjob_41de6a2f_18728cf1999.csv"))## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_sqtl` where variant_id like "chr5_96900192%" order by pip desctauras_snp =read_csv(glue("{DATA}/bquxjob_719c0131_18728db8878.csv"))## finemapping for the intron affected by chr5_96900192## SELECT * FROM `gtex-awg-im.GTEx_V8_DAPG.variants_pip_sqtl` where gene_id like "intron_5_96900189_96901506" order by pip descintron =read_csv(glue("{DATA}/bquxjob_41bc6351_18728e4ee94.csv"))##intron %>%filter(tissue=="Cells_EBV-transformed_lymphocytes") %>%arrange(desc(pip))## ## erap2 %>% filter(pip>0.1) %>% group_by(variant_id) %>% summarise(sumpip=sum(pip),ntissues=n()) %>% ggplot(aes(variant_id,sumpip)) + geom_bar(stat = "identity") + geom_point() + ggtitle("ERAP2 expr: most tissues assign pip to 16728 & 16885")erap2 %>%filter(pip>0.1) %>%ggplot(aes(variant_id,pip)) +geom_violin() +geom_boxplot(width=0.05,alpha=0.5,outlier.shape =NA) +geom_point() +ggtitle("ERAP2 expr: most tissues assign pip to 16728 & 16885") +ylim(0,NA)print("intron intron_5_96900189_96901506 ")intron %>%filter(pip>0.1) %>%ggplot(aes(variant_id,pip)) +geom_violin() +geom_boxplot(width=0.05,alpha=0.5,outlier.shape =NA) +geom_point() +ggtitle("ERAP2 intron_5_96900189_96901506:") +ylim(0,NA) +coord_flip()#intron %>% filter(pip>0.1) %>% group_by(variant_id) %>% summarise(sumpip=sum(pip),ntissues=n()) %>% ggplot(aes(variant_id,sumpip)) + geom_bar(stat = "identity") + ggtitle("ERAP2 intron_5_96900189_96901506: ") + coord_flip()#ggplot(aes(variant_id,sumpip)) + geom_bar() ```Causal SNP according to the black death paper and others is rs2248374 chr5_96900192