sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
14fc6a88aeece9ff4f3347bdb949e30d00aed44d5191600994c8f8f0a9121596 | SAS | 6,477 | 256 | %macro tabulate4cutoff(
dsd,
byids,
target_var,
target_cutoffs,
step,
dsdout,
ge_or_le,
draw_fig4passed_tot=0, /*draw scatter plot with its y-axis for the total number of samples passed the target_cutoffs;
otherwise, it will draw the figure using the % of samples passed the target_cutoffs*/
sumary_fig_ht=1000... |
e71c075b3be421a4472fcb7845b0233f58d691a0fdac77edb3689131b7605fe8 | SAS | 6,577 | 279 | %macro deseq_normalization_slow(
dsdin,
read_vars,
dsdout,
readcutoff=3,
cellcutoff=5
);
/*readcutoff and cellcutoff will be used to exclude genes NOT passing the filters:
at least the number of cells expressing at least the number of reads*/
/* options compress=yes; */
*The length of the value of the macro variable R... |
360bae3411a9a2331069195537dd91241e75faa4ca4f1b4c2f0c9f794fa8ab83 | SAS | 6,640 | 229 | %macro IdentifyBedClusters(bedin,chr_var,st_var,end_var,bedout,dist=0);
/*Note: the input bed should have regions with st < end position and from
the same or different chrs or groups!*/
/*Try to lookup the st pos of each bed region with other regions in the same bed*/
/*the a.&st_var^=b.&st_var is important to ... |
e389d0bbacd71130210888fb6544933ed2820787687d60b8c45a7635f2832cfb | SAS | 6,649 | 192 | %macro SQ_DROPMISS( DSNIN /* name of input SAS dataset */
, DSNOUT /* name of output SAS dataset */
, NOCOMPRESS= /* [optional] variables to be omitted from the minimum-length computation process */
, NODROP= /* [optional] variables to be omitted from droping even if they have only ... |
127739d525e619abd94a3c023552be16b0ba177fe186d17c6186b3c9e5e5ee7b | SAS | 6,664 | 216 | %macro Caculate_eQTL_in_GTEx(
/*Please use CaculateMulteQTLs_in_GTEx to replace this macro*/
query_snp=rs13057307,
gene=Apobec3a,
genoexp_outdsd=genoexp,
eQTLSumOutdsd=AssocSummary,
filter4geno= /*provide sas where or if condition to filter genotype data
such as %str(where geno^=0;) */
);
%QueryGTEx4GeneID(
geneids=&g... |
209f28b3413fc120a6cb9886058f71dbcc11e923c0c41169663d0e0e9b93111e | SAS | 6,754 | 248 | %macro bed_region_plot_by_grp_splitted(
bed_dsd,
chr_var,
st_var,
end_var,
grp_var,/*bed regions will be colored according to the group membership*/
val_var4bed_reg,
indv_var,/*If empty, the macro will draw bed regions without considering individual information*/
inethickness=20
);
*Note: this macro will make... |
003f2281af6fd6db3639a19157d18abff6fb0831ab1d277f59628d9e04bf03a9 | SAS | 6,931 | 243 | %macro make_fake_axis_values4grps_new(
dsdin,
axis_var,
axis_grp,
new_fake_axis_var,
dsdout,
yaxis_macro_labels=ylabelsmacro_var
);
*Fix a bug when only one record in a group;
*make an extra copy for the records to make it has >1 records;
*This is because the script will not be able to update corrected;
*y... |
d8ae47cc638b260a3d75d74e834cac634cfb6d792d2f694852a083b9b4a13ab3 | SAS | 6,959 | 232 | %macro needleplot4snpsdiffzscores(
diffzscore_gwas,
gwas1_z,
gwas2_z,
snp_var,
snps,
diffzscore_p_var,
gwas1pvar,
gwas2pvar,
fig_height=400,
fig_width=600,
NotDrawBubbleBySize=0, /*Draw common bubble plot with the same size of bubbles*/
transparency4needles=0.6,
keep_snp_order4xaxis=0,
draw_p_axis_by_z_direction=1, /*D... |
ed45e0f64d831f9792a5a2dea2f7e3dfd960604c4032b5887b90366101b0683a | SAS | 6,970 | 272 | %macro PrepareDsd4MutRegPlot(
dsd,
pos_var,
ID_var4yaxis,
x_st4mut,
x_end4mut,
gr4color,
pic_wd,
pic_ht,
dot_size,
dsdout,
seriesplot=0,
yoffsetmin=0.01, /*Adjust the y-axis offset min or max to prevent the axis overlap with barplot*/
yoffsetmax=0.01,
xoffsetmin=0.01,
xoffsetmax=0.01,
colors4grps=CXd178... |
ed11c10f8b92be67ca8fba87f575a0816900e2365429b95e79249520aa1d241e | SAS | 6,983 | 295 | %macro gwas_manhattan_pipeline(
GWAS_File,
Marker_Col_Name,
Marker_Pos_Col_Name,
Xaxis_Col_Name,
Yaxis_Col_Name,
Marker_X_Xpos_Y_ColNums,
GWAS_dsdout,
gwas_thrsd,
OutDir,
Replace_Previous_Rst=1,
Numeric_Xaxis_Col=1
);
%let Marker_Col_Name=%assign_str4missing(Inval=&Marker_Col_Name,NewVal=SNP);
%let Xaxis_Col_Name... |
a9e04d2d087c4f442b7b32d6ca168d030d85c5edaeda7a6ca46e55adc375ba49 | SAS | 7,085 | 279 |
%macro ImportSpecCols4FilesInDirbyScan(
fileDir /*raw data file dir*/
,fileRegexp /*regexp to match files*/
,dsdout /*SAS output dataset name; N.B.: All variables are in character!*/
,firstobs=0 /*The line number for header; if there is no header, firstobs=0*/
/*if the header is at 3... |
476f42e868f189d09a99a180d7be19f892f1a9780363fa576652653a527032c9 | SAS | 7,098 | 248 | %macro gwas_top_hits_manhattan(
GWAS_File=,
Marker_Col_Name=,
Marker_Pos_Col_Name=,
Xaxis_Col_Name=,
Yaxis_Col_Name=,
Marker_X_Xpos_Y_ColNums=,
GWAS_dsdout=,
gwas_thrsd=,
Mb_SNPs_Nearby=,/*this Mb_factor will multiple 1,000,000 when running in the program*/
OutDir=
);
%let Marker_Col_Name=%assign_str4mis... |
1da7798fcccc647c7ed20fb7b80e3f53b120dc0d5d3c8b458c20f9b85a2d6749 | SAS | 7,205 | 292 |
%macro ImportFilesInDSDbyScan(filedsd /*sas dsd containing filenames*/
,filename_var /*filename variable in the above dsd*/
,fileDir/*raw data file dir; if using fullpath in dsd,let it empty*/
,fileRegexp /*regexp to match files*/
,dsdout/*SAS output dataset name; N.B.: All var... |
bad9523150993a0ac472d9f7213dee71120acefba75466467ff07bf5c011a32d | SAS | 7,230 | 225 | %macro VarscanIDs2Annovar(VarscanID_dsd,
Tbl_or_File,
VarName,
dsdout,
annovar_input,
annovar_dir,
annovar_outdir,
Anno_dsd_... |
dae5717eb22f0e52ed6a9695eb46b3fc0f1680214414b59e3d2a116f95d92fb2 | SAS | 7,238 | 234 | %macro tree_CL_positions(
data=, /*A typical output generated by proc cluster*/
child=child, /*Equivalent to y_name_ or x_name_ from proc cluster; ensure there is not spaces
included in the elements of this variable!*/
parent=parent, /*Equivalent to y_parent_ or x_parent_ from proc cluster*/
hh=hh, /*Equivalent... |
7fb23df9c29511fcef327c55b25d0ab0d677c0b3c3bcd7a38a3e1680edd92474 | SAS | 7,287 | 216 | %macro sorted_barplot(
grpdsd=, /*input dataset for making sorted barplots by the values of a grp variable*/
grp_var=ID, /*character groups for x-axis, thus if no extra color variable supplied for the last paramter colorgrp_var,
the macro will draw ALL bars in different colors, which sometimes is not informative!*/
... |
3ee4798af22d17d2bc24ac76f599cdcb336b68f7c32c0c99fbd1007bdc9ada64 | SAS | 7,314 | 212 | /*
gwas_names:
such as A1_ALL, B1_ALL, B2_ALL, and C2_ALL;
furthermore, except B1, all others have subpopulation GWASs,
such as B2_AFR, B2_EAS, B2_SAS, B2_EUR;
Note: A2_HIS, C2_HIS and B2_HIS tar gz file was broken
Also include long covid GWASs from locuszoom: LC_W1, LC_N2, LC_W2, and LC_N1;
Long COVID HGI - DF4... |
1a78c91ce37b84c5fbe56111e0677f5b033fa80d4d65b1aa9dc07e0a938a9fc0 | SAS | 7,328 | 190 | %macro towide(longdata,widedata,id,suffix,suffixlo,suffixhi,vars,types=,lengths=,numprint=,quiet=,sorted=);
/*
longdata - name of input data file that is in long form
widedata - name of output data file that will be in wide form
id - variable that uniquely identifies the wide records
suffix - va... |
ccaa4b8bbd08178b1b4fe9b2dabb8a9eb9bfb9d32116d099d7bcf8dfd2559466 | SAS | 7,362 | 235 | %macro spaceAdjust(
/*
This macro can generate new numbers by adjusting its distance space
in the sorted numbers, so please ensure the input dataset containing
numbers that are sorted in ascending order; if the input is a list, the macro
will generate a sorted dataset and generate adjust numbers automatically.
*/
dat... |
727128bf71b9ed2f2dd981614ed4d859fc394bc9d06f8eb059230c679fd225ba | SAS | 7,484 | 224 | %macro adjust_close_positions(
/*Limitation: where there are only 2 closely related positions, a fixed distance with Pct4OnlyTwoPos*step will be used to separate them;
Additonally, if there are positions too close to the start or end of position in the figure, it is possible to modify the internal macro
var pct2adj4... |
5bfe13e20e6c21b0bf74e3c511e0c44a60dbab47c88530120d69c86730322778 | SAS | 7,611 | 271 | %macro make_fake_axis_values4grps1(
dsdin,
axis_var,
axis_grp,
new_fake_axis_var,
dsdout,
yaxis_macro_labels=ylabelsmacro_var
);
*Fix a bug when only one record in a group;
*make an extra copy for the records to make it has >1 records;
*This is because the script will not be able to update corrected;
*y axis labels if... |
88129684d5c8fedd70e1f947a0421b20f9792de7689bc1634ab05f2e08a3113d | SAS | 7,653 | 255 |
%macro GTEX_SexBasedDiffGeneHeatmap(GTEx_sex_gz_file,gtf_dsd,st,end,chr,vars4sortheatmap);
/**The downloaded file with multiple files included in the subdirectory, SAS will miss the file headers for these compressed data*/
/* https://www.gtexportal.org/home/datasets */
/* %let file_url=https://storage.googleapis.com/... |
fd135242547edb68a424da6cd0caca161497dfd6d407602f2123b26d4cf7ee41 | SAS | 7,727 | 226 | %macro _is_sas_macro(file=, bytes=8192, mv=IS_SASMACRO);
%if "%sysfunc(strip(&file))" ="" %then %do;
%put NOTE: (is_sas_macro) FILE= was blank, so this candidate will be skipped.;
%let &mv = 0;
%return;
%end;
%global &mv;
%let _exists = %sysfunc(fileexist(%sysfunc(dequote(... |
220573f12350181a54fc2be6e98de4c181d132373efb8ed7262b7ad138ffaea9 | SAS | 7,731 | 270 |
%macro Mult_BED_Enrichment(bed_db,
query_db,
query_var_name,
random_db,
random_var_name,
np,
sampling_dsdout,
fdr_dsd_out,
by_var4bed_db,
output_mut_summary,
Uniq_match_only
);
/*only count unique match when query columns in d... |
2daf787e37ff427a04fa6da2ee26c6f1fd42ff9a44bdb351b9112fbe4db7517f | SAS | 7,768 | 247 | %macro Beta2OR_forest_plot(
dsdin=,
beta_var=,
se_var=,
sig_p_var=,/*adjust the threshold of p in the extra_condition4updatedsd*/
marker_var=,
marker_label=,
svgoutname=,
figfmt=png,
figwidth=600,
figheight=800,
dotsize=10,
autolegend=0,
xaxis_value_range=%str(0.4 to 1.6 by 0.2),
sort_var4y=,/*Provide a v... |
b20639f842b6d4b8fe5d7450120c068a4c45f25e9bd5c93669e581e7b2c18981 | SAS | 7,885 | 271 | %macro make_fake_axis_values4grps_old(
dsdin,
axis_var,
axis_grp,
new_fake_axis_var,
dsdout,
yaxis_macro_labels=ylabelsmacro_var
);
*Fix a bug when only one record in a group;
*make an extra copy for the records to make it has >1 records;
*This is because the script will not be able to update corrected;
*y... |
644526885b7935acdb893c747e38985e9ff3656d88aa50cb963b6c46099662f3 | SAS | 7,901 | 306 | /*
A SAS Macro for doing semiparametric regression of multi-dimensional
genetic pathway data, using least squares kernel machines and linear
mixed models.
https://content.sph.harvard.edu/xlin/software.html
Liu, D., Lin, X. and Ghosh, D. (2007) Semiparametric Regression of Multi-Dimensional Genetic Pathway Data: ... |
e56e6e866344ddeb24b33508cd94d17177134ed16adbc5bc6c88f0b042491700 | SAS | 7,917 | 201 | %macro random_import_cell_mtex(
/*Funcational annotation: this macro is suitable for columns more than 1 million, which is relative faster than other similar macros;
For subsetting smaller % of columns, the macro seems to be not better than the macro random_import_cell_mtex4smalldsd!*/
gzfile=,/*the fullpath to comp... |
f93ed378f36c6de817d01c689635d9e323bf7d74aa49ff866ea9a155b91d86de | SAS | 8,042 | 241 | %macro longformdsd4heatmap(
/*Compared to the macro heatmap4longformatdsd, this macro may not be good enough!
whenever possible, please use the heatmap4longformatdsd! The macro is kept for
code reusing purpose!*/
dsdin,
row_var,
col_var,
value_var,
value_upperthres,
Newvalue4upper,
value_lowerthres,
Newvalue4lower,
cl... |
6acb76c1398f4e56711b8a89e29543a3c83948ed13b75f1de81f53215e0faa01 | SAS | 8,082 | 275 | %macro _make_fake_axis_values4grps_(
dsdin,
axis_var,
axis_grp,
new_fake_axis_var,
dsdout,
yaxis_macro_labels=ylabelsmacro_var
);
*Fix a bug when only one record in a group;
*make an extra copy for the records to make it has >1 records;
*This is because the script will not be able to update corrected;
*y a... |
c5855e2fb3162ad875ee3fe91886d7674a7311848300306cd8b9407cc7c2c924 | SAS | 8,186 | 228 | %macro GTEx_Hap_eQTL_Analyzer(
/*If there is not plink prunned snps available, please use SAS macro Haplotype_Analysis4SNPs_in_GTEx by following its demo codes*/
SNPs4Haplotype=rs7872943 rs1887428 rs1887429 rs59679286 rs5938437 rs10974914 rs1576271, /*SNPs for haplotype eQTL analysis*/
plink_prunned_snp_file=H:\D_Qu... |
8cf7bd709f1be7e36408c42b8a0e2e9ca3f092df54f131f0b37be4e02eb78927 | SAS | 8,193 | 253 | %macro ucsc_cell_matrix2wideformatdsd(
/*Note: this macro can also import large table with 1st column is gene and others for sample exp!*/
gzfile_or_url,/*Can be url for gz or plain text or tsv file; also, it can be a fullpath for these files in local computer*/
dsdout4headers,
dsdout4data,
extra_cmd4infile=,/*It ... |
32f9a97b99268a69c05495ae62b3a559596d56b3a7322c52b4a57d4d428ac348 | SAS | 8,239 | 246 | %macro subbranches(
data=, /* input dataset, which should
contain the following 3 input vars:*/
y_name_var=y_name_,
y_parent_var=y_parent_,
y_height_var=y_height_,
out=work.sub, /* output dataset */
height=, /* numeric cutoff (use either height= or parent=), and only the
t... |
813a0da0f5638aaaa6b6b8cf7a085b986776b4c2e9e362315ac3293d66d038b6 | SAS | 8,348 | 259 | /*
The macro has been changed to read sas dataset directly by Zhongshan Cheng;
A SAS Macro for estimating and testing for the effect of a genetic pathway
on a disease outcome using logistic kernel machine regression via logistic
mixed models.;
https://content.sph.harvard.edu/xlin/software.html
Liu, D., Ghosh, ... |
ff73ea730c9f58978d940c46730d436db59b4b59e4441f8ac1f8bf3212409123 | SAS | 8,553 | 286 | %macro MutRegOverlappedBlock(
block_dsdin
,block_chr_var
,block_st_var
,block_end_var
,chr
,mindist
,maxdist
,Mut_dsdin
,Mut_chr_var
,Mut_st_var
,mut_sample_var
,Final_dsdout
,block_filcolor
,block_filaltcolor
,dotsize
,dotcolor
,max_y
,add_sample_ref_line=0
,graph_designwidth=400
,graph_designheigh... |
ca57d0f0b82fb858e4235a09fb93e1ac6d6a5fad27bbd79430b1d9f51fa0bfb4 | SAS | 8,641 | 228 |
/* -----------------------------------------------------------------------
Program : Tmplt.sas
Purpose : Generate a template for multiple plot displays.
Also embed the TREPLAY macro so that it can be invoked
as an option to replay plots lockstep through the newly
... |
4fce829d1af55a584ac4d5bf90b96cacce702f78be31fe8485ccf354697caf7e | SAS | 8,736 | 327 | %macro heatmap4longformatdsd(
/*Note: the easiest way to sort the x and y axis with customized order is to
pre-sort the dsdin according to specific xgrpvar and ygrpvar in user customized order
i.e.: proc sort data=dsdin;by xgrpvar ygrpvar;run;
These two grp vars can be generated by proc sql with specific conditions... |
5bba79a74b879c7e3325c8aa7d18db7b6f606fddfcae0fb0bc5bf6b9f0cd446a | SAS | 8,765 | 285 | /*
For linux: sasv9_usermods.cfg
/usr/local/SASHome/SASStudioBasic/3.4/template_usermods/workspaceserver/sasv9_usermods.cfg
but it doesn't work
The only way to solve the problem is put user macros into sasautos dir
sudo cp /home/zhongshan/TCGA_Paper_Scripts/NewSASMacros/* /usr/local/SASHome/SASFoundation/9.4/sasautos... |
51dbd39d17013756deca7f40f6d2e8dde04cd1e72481aec0afc7bd475bdc7528 | SAS | 8,891 | 331 | /*Note: this macro is only able to import HGI GWAS release 7;*/
%macro ImportHGICovidGWASFromHGI_R7(
zip,
filename_rgx,
sasdsdout,
deleteZIP,
for_subpop=0 /*R7 GWAS for ALL and sub-populations are in different format*/
);
%local nfiles txtfilenames txtfilename;
/*CHR POS REF ALT SNP
all_meta_N all_inv_var_meta_beta
... |
1ec006e83ed9c1c2a195076ca101762f899006e4953e70ad03c87ae3323ff08a | SAS | 9,178 | 209 | %macro SQUEEZE_1( DSNIN /* name of input SAS dataset */
, DSNOUT /* name of output SAS dataset */
, NOCOMPRESS= /* [optional] variables to be omitted from the
minimum-length computation process */
);
*This macro is the original version of SQUEEZE.sa... |
7466f51f879fa400b9561d88522f2dc44360da35554b9c5bf9b2df7d9801b298 | SAS | 9,214 | 317 | %macro sc_umap(
umap_ds=umap,
xvar=x,
yvar=y,
cluster_var=cluster,
sample_grp_var=,
ordered_sample_grps=,/*Provide ordered group names here to generate subplots in the same order as in this macro var*/
down_sampling_num=1,/*
Provide pct value ranging from 0 to 1 or
number of cells
to get random cells for dow... |
567b6f215d50e63adda48e7b09b0529cfb18407734fdce6640c13f9f2662c0a8 | SAS | 9,229 | 294 | %macro UKB_Female_vs_Male_GWAS_Pipeline(
female_gwas_url,
male_gwas_url,
female_male_gwas_url,
outdir=/home/cheng.zhong.shan/my_shared_file_links/cheng.zhong.shan/F_vs_M_Covid19_Hosp,
forece=1
);
*Use EUR COVID19 GWAS;
/* %let GWAS_F_url=https://grasp.nhlbi.nih.gov/downloads/COVID19GWAS/06182021/UKBB_hsptl_EUR_F_061821... |
6c7089a7509d5542b0981d00447bdb529f66e0915bc4359c62b089845165ea6a | SAS | 9,286 | 335 | %macro Get_Tested_ASE_Muts(
Cancer,
normal_aaf,
gene,
MatlabAnalysisDir=F:\NewTCGAAssocRst /*This is the matlab analysis directory containing directories for different cancer types,
and each cancer directory has the following subdir: MatlabAnalysis*/
);
%if &gene ne %then %do;
%put Will only query ASE-Mut for ... |
e99765690a6570fffb09e0b81a7ad4d1e0b87256e15a8aa155cb677088531f0b | SAS | 9,305 | 351 | %macro Boxplots4GenesInGTExV8ByAA(
genes=MAP3K19 R3HDM1 CXCR4 DARS LCT UBXN4 MCM6 ZRANB3 RAB3GAP1 CCNT2 ACMSD TMEM163,
dsdout=exp,
UseGeneratedDsd=0,
PreviousDsd=tgt,
Lib4PreviousDsd=GTEx,
WhereFilters4Boxplot=%str(),
boxplot_width=800,
boxplot_height=1000
);
%let gene4sort=%qscan(&genes,1,%str( ));
%if &boxplot_heigh... |
e9c8d13cd4ed9f60483035d79c6fae8db44dd2af00679b364bff53469843a480 | SAS | 9,455 | 295 | %macro make_fake_axis_values4grps(
/*This macro has issue when axis_var containing positve and negative values among different grps*/
dsdin,
axis_var,
axis_grp,
new_fake_axis_var,
dsdout,
yaxis_macro_labels=ylabelsmacro_var,
step4yaxis_macro_labels=1,/*Only keep ticks with mod(t,step)=0, which will prevent the ... |
5c141b1eb1e8c6a30511fc326d6af00775a783c0b701c937752c26e2cc242022 | SAS | 9,480 | 390 |
*options mprint mlogic symbolgen;
%let macrodir=%sysfunc(pathname(HOME))/Macros;
%include "¯odir/importallmacros_ue.sas";
%importallmacros_ue;
%mkdir(dir=%sysfunc(pathname(HOME))/data);
libname D '%sysfunc(pathname(HOME))/data';
%let gwas_url=https://grasp.nhlbi.nih.gov/downloads/COVID19GWAS/10202020/COVID19_HGI_... |
8edb5a464850c96b832dec0cb262dd18022434e4203eb485986dd974b84f8421 | SAS | 9,516 | 367 | %macro HGI2PairwiseGWASPipeline(
gwasfile_dir=F:\360yunpan\SASCodesLibrary\SAS-Useful-Codes\Macros,
gwas1gzfile=COVID19_HGI_B1_ALL_leave_23andme_20210107.b37.txt.gz,
gwas2gzfile=COVID19_HGI_B2_ALL_leave_23andme_20210107.b37.txt.gz,
EUR_AFR_frq_file=EUR_AFR_specific.txt,
tgt_snps=12:113357193:G: 17:44219831:T:A 19:... |
5164a11119cba07c377743574d5aa91ee6f3c33cdd9109b651b7eb64d45a5c96 | SAS | 9,544 | 264 | %macro local_multigwas_manhattan(
GWAS_SAS_DSD=,
Marker_Col_Name=,
Marker_Pos_Col_Name=,
Xaxis_Col_Name=,
Yaxis_Col_Names=, /*Support multiple p-val vars*/
GWAS_dsdout=,
gwas_thrsd=, /*-log10(P) threshold, such as 5*/
Mb_SNPs_Nearby=,/*this Mb_factor will multiple 1,000,000 when running in the program*/
snps=,
design_w... |
7fb875f355983295f83b0bcc61533e12cbab060373f862f6caaa4c813cfd939f | SAS | 9,615 | 335 | /***********************Important********************************************;
*Note: for typical microarrays with thousands of genes,;
*the simplely running of glimmix will not be computational feasible;
*because of the large size of the X matrix;
*In this situation, we recommend breaking the model into two parts:;
*t... |
7d26c3404c92c68040f7f6dfe63866a49dfc7cbe1d5be1799d7e069dca0d988c | SAS | 9,622 | 314 | %macro Bed4BlockGraphByGrp(
dsdin,
mindist,
maxdist,
chr,
chr_var,
st_var,
end_var,
dsdout,
graph_wd,
graph_ht,
show_block_values,
Grp,
block_colors=darkred darkblue,
gap_color=white
);
/*make sure no overlapping between each bed region*/
%local i block_values grp_list grp_n color xi gi;
/*typical c... |
a8a9732a99c8fe3ea13d47cbc3e2b31e364bc6a9573874f8cacf16cc28be57ac | SAS | 9,718 | 317 | %macro scatter_over_bed_track(
bed_dsd,
chr_var,
st_var,
end_var,
grp_var,
yval_var,
yaxis_label=Group,
linethickness=20,
track_width=800,
track_height=400,
dist2st_and_end=0,
dotsize=10
);
*A new numberic group, ord, is created in descending order;
*Note: it is important to sort the group by yval_var ... |
d35edc8b27d83269e221125544afb97295ac1f70215a4554c701e8f01e0c3a6b | SAS | 9,865 | 327 | %macro gscatter_over_bed_track(
bed_dsd,
chr_var,
st_var,
end_var,
grp_var,
scatter_grp_var,
yval_var,
yaxis_label=Group,
linethickness=20,
track_width=800,
track_height=400,
dist2st_and_end=0,
dotsize=10
);
%if &scatter_grp_var eq %then %do;
%put Please provide the variable for scatter_grp_var, as it is empty!;
%a... |
8d407bb5ea32aaefbf95da4e51cedcc8680edc0383ebeb9c7846583db336b3e4 | SAS | 9,868 | 376 | %macro deseq_normal_not_optimized(/*for backup purpose*/
dsdin,/*Note: to save space, the input dsd will be replace*/
read_vars,
dsdout,
readcutoff=3,
cellcutoff=5
);
/*readcutoff and cellcutoff will be used to exclude genes NOT passing the filters:
at least the number of cells expressing at least the number of reads*/... |
ee15b3b9c8d9f150ef3b98f76049b88195829d37c9404fe173a7a4fceb9dba28 | SAS | 9,941 | 363 | *This macro is replace by deseq_normalization;
*as the old one takes too much resource and memory;
%macro deseq_normalization_old(
dsdin,
read_vars,
dsdout,
readcutoff=3,
cellcutoff=5
);
/*readcutoff and cellcutoff will be used to exclude genes NOT passing the filters:
at least the number of cells expressing ... |
e9778e3c52f7a2c6a2f1276a528f08bba152fa71f2294bf21e8996ca0e675b93 | SAS | 10,032 | 232 | %macro DIRLISTWIN( PATH /* Windows path of directory to examine */
, MAXDATE= /* [optional] maximum date/time of file to report */
, MINDATE= /* [optional] minimum date/time of file to report */
... |
c598d8ad177f0912474efce360e48efc7c2abead7719f50f4a86fc613c0b89ab | SAS | 10,282 | 395 | %macro Bed4BlockGraph(
dsdin,
mindist,
maxdist,
chr,
chr_var,
st_var,
end_var,
dsdout,
graph_wd,
graph_ht,
show_block_values,
block_color=CX0000FF, /*color for the bed block regions*/
gap_color=CXFFFFFF /*color for the space regions between bed regions*/
);
/*make sure no overlapping between each bed reg... |
5572fe5db3331b5aa7483b258fa81a2622bd8a8063ff99352c6f3b7b0cac66e0 | SAS | 10,480 | 339 | %macro review_tree_branches(
inputdsd=a,
y_name_var=child,
y_parent_var=parent,
y_height_var=hh,
outdsd=out,/*A output dataset would be further used to draw new tree with sgrender template HeatDendrogram1*/
branch_name_dsd=branch_name_dsd /*Ordered branche names for the end leaves in the final cluster from left t... |
f37a984a9620c1baeebf56f80ce99da124132ea6f7966160298070865236702e | SAS | 10,557 | 392 | *Note: this macros is the old version as it only can handle single GWAS;
*For better performance, it is suggest to use the following macro, which can plot multiple GWASs;
*Manhattan4DiffGWASs.sas;
* macro that can be used later to generate symbols for plots with two alternating colors;
%macro twocolors(c1,c2);
%do j=1... |
dbd18c679f310674953050a7428fd43894cacf1ba9968f57a02eb6d68561d31d | SAS | 10,668 | 319 | /*
/ Program : xl2sas.sas
/ Version : 1.0
/ Author : Roland Rashleigh-Berry
/ Date : 03-Feb-2008
/ Purpose : Read an html Excel spreadsheet into a sas dataset using DDE
/ SubMacros : none
/ Notes : This is meant to be run interactively. The start and end rows
/ ... |
b1bf640468b9a6f9798f5e2c4974555da85218192a4413cba29441c5138a84e0 | SAS | 10,832 | 266 | %macro SQUEEZE( DSNIN /* name of input SAS dataset */
, DSNOUT /* name of output SAS dataset */
, NOCOMPRESS= /* [optional] variables to be omitted from the
minimum-length computation process */
);
*Note: this macro was updated by zhongshan to gen... |
8d55abe53313a82a9cb9dfd7bcc8244411ef33f81b4150ef27c3366a8c7832f3 | SAS | 10,988 | 347 | %macro InstallGitHubZipPackage(
git_zip=https://github.com/chengzhongshan/COVID19_GWAS_Analyzer/archive/refs/heads/main.zip,
homedir=%sysfunc(pathname(HOME)),/*SAS OnDemand for Academics HOME folder*/
InstallFolder=NewMacros, /*Put all uncompressed files into the folder under the homedir*/
DeletePreviousFolder=0, /... |
c44433ebab9a17cde232521c8ddde450813264cf280cebb81034ff717cef7a2f | SAS | 11,014 | 353 | %macro GTEx_eQTL_genes_scatterplot(
genes=Apobec3a Apobec3b,
hg38_gtf_dsd=FM.GTF_HG38,
eqtldsdout=tgtgenewidedsd,
min_pos= ,/*restrict the start position in hg38 of local Manhattan plot;
If it is empty, default value would be the minimum start position;*/
max_pos= ,/*restrict the end position in hg38 of local Manhatta... |
723b86dbbe48c1c5b6f1b6ee46a974e4a6380ff6f7c7fc42f2380922defdc11a | SAS | 11,079 | 322 | %macro FisherTestGenomeWide(
/*Note: Please use the macro two_cohorts_mut_fisher_test to replace this macro!
this macro will use unique sampleID and pheno_var to make all to all combinations,
please make sure the input table contain all target sampleID and pheno_var;
If not, please supply a sas dataset containing ... |
3ac9bbed8ec977a3cc79a5340ad6c046f8dcf761f990d211db3e8cdb5baac15f | SAS | 11,147 | 417 |
%macro GWAS_Merge_1KG(
OneKG_Path,
OneKG_Pop,
PLINK_EXE,
WorkDir,
User_Imput_GWAS
);
/*In case of input of multiple populations*/
%let re=%sysfunc(prxparse(s/ +/" "/oi));
%let pop_list="%sysfunc(prxchange(&re,-1,&OneKG_Pop))";
%put OneKG_Pops: &pop_list;
%syscall prxfree(re);
%let OneKG_Pop=%sysfunc(prxchange(s/\s+/... |
578c7ac2f5564b06f0b4ba61d1a8c27335467baf68c500d40422f0ac20553b54 | SAS | 11,457 | 291 | %macro local_gwas_hits_and_nearby_sigs(
/*Note: this macro is only works for top GWAS hits with p < 1e-6, as it
requires to have the top independent SNPs as input for the var snps;
However, there are still bugs as the output figure is abnormal for the
center marker of the topest snp;
somethings are wrong with th... |
17ce8065093a39a86e28f7a97478b64c9d36d72582551ea7a19a3e479102eef0 | SAS | 11,609 | 335 | %macro Haplotype_Analysis4SNPs_in_GTEx(
query_snps=rs7850484 rs17425819,
gene=GAPDH,
genoexp_outdsd=genos,
eQTLSumOutdsd=AssocSummary,
rgx4tissues=, /*optional regular expression to select specific tissues for haplotype association;
such as (lung|liver) */
filter4geno= %str(where geno^=-1) /*put conditional filt... |
073562b1c90e8ee1686faeb9d54edf6fc8c2d120fa8a3c9dc9786087cc878a64 | SAS | 11,639 | 348 | %macro UKB_Female_vs_Male_GWAS_GRASP(
/*this macro is ONLY able to process GWASs regardless of sex from both GRASP COVID-19 database;
This means the two input GWASs can be any GRASP GWASs with potential biological differences for further investigation;
for example, it can be used to perform differential GWAS between AF... |
6fed3bcba85d2a8952e6e645008d5f118130b9c3b8c622b642fce4942340ae60 | SAS | 11,646 | 369 | %macro sc_scatter4genebygrp(
dsd=,
dsd_headers=,
dsd_umap=,
gene=,
pheno_var=,
pheno_categories=,
grpvar4boxplot=,
samplewide=1,
sample_var=sample,
boxplot_width=1000,
boxplot_height=600,
boxplot_nrows=3
);
/* libname sc "/home/cheng.zhong.shan/data"; */
*Need to have sc.exp, sc.UMAP;
%let ncats=%ntokens(&pheno_categor... |
afcbcd48f321f6adf893f634b0a8997d3a9c3de8cb15024d3e7deb2317fa923a | SAS | 11,840 | 353 |
%macro DiffTwoGWAS(/*Note: only common SNPs will be kept;
also requires to have two allele vars common to both GWASs:
such as allele1 and allele2 in both GWAS;
duplicate snps in each GWAS will be excluded
Important: it is necessary to sort the two input GWAS by chr and pos before
applying current macro!
*/... |
f88a08a05ea96a8bb3f4724d173def7d5f40766a4813f2375923eba210100614 | SAS | 11,989 | 436 | %macro Boxplots4GenesInGTExV8(
genes=MAP3K19 R3HDM1,
dsdout=exp,
bysex=1,
UseGeneratedDsd=0,
PreviousDsd=tgt,
Lib4PreviousDsd=GTEx,
WhereFilters4Boxplot=%str(),
boxplot_width=1200,
boxplot_height=1000
);
%if &boxplot_height eq %then
%let boxplot_height=%eval(250*%ntokens(&genes));
%let gene4sort=%qscan(... |
fb99efaa7d026063ef28712a783c35ffa342ad3e018de1552d3c866403876fd6 | SAS | 12,495 | 396 | %macro ImportFileHeadersFromZIP(
zip=,/*Only provide file with .gz, .zip, or common text file without comporession
Note: it is necessary to have fullpath for the input file!*/
filename_rgx=.,
obs=max,
sasdsdout=x,
deleteZIP=0,
infile_command=%str(firstobs=1 obs=10;input;info=_infile_;),
/*Better to use nrbquote... |
ec47b457ac6a4ca7709d1f4abe6f2c6d5439b974134377446d2b609ef8d62a1c | SAS | 12,538 | 447 | %macro deseq_normalization(
dsdin,/*Note: to save space, the input dsd will be replace*/
read_vars,
dsdout,
readcutoff=3,
cellcutoff=5
);
/*readcutoff and cellcutoff will be used to exclude genes NOT passing the filters:
at least the number of cells expressing at least the number of reads*/
*Alternative way ... |
7c2c74c773bc598c1c5f9aae2c444be4c9c33f933fb45b846ff1736645182d0f | SAS | 12,610 | 382 | ***********************************************************************************************************************
***********A macro that execute R scipt in base SAS********************************************************************
** MACRO Version: 1.0 ... |
12704167d5caecd8c62e17b4a1a8a66bec214a05ee75a0b78660b6aba7c3dd30 | SAS | 13,019 | 308 | /* MACRO %GetVarList
Version: 2.01
Author: Daniel Mastropietro
Created: 27-Dec-2004
Modified: 20-Jun-2016 (previous: 17-Aug-2006)
DESCRIPTION:
This macro parses a list of variables in a dataset by converting the keywords
_ALL_, _NUMERIC_, _CHAR_, hyphen strings (such as in x1-x7, id--name), and colon refere... |
a35dc5f69f3e48245c94b4dcbf07064bcb9f9cbf8b1f3a7b6a186202c6576b81 | SAS | 13,570 | 281 | %macro get_HGI_R7_GWAS(
gwas_name=, /*such as B1_ALL, B2_ALL, and C2_ALL;
furthermore, except B1, all others have subpopulation GWASs,
such as B2_AFR, B2_EAS, B2_SAS, B2_HIS;
Note: A2_HIS, C2_HIS and B2_HIS tar gz file was broken! No A1_ALL
Only SNPs with het_p>0.05 will be kept!
*/
hgi_gwas=hgi_gwas_out, /*sas ... |
ce9eef58772de90e38ad46b22c29d193a5ee8f4c2e1eb2ad829b5825df94408a | SAS | 13,756 | 399 | %macro UKB_Female_vs_Male_GWAS_Pipeline(
/*this macro is able to process GWASs regardless of sex from both Neale lab and GRASP COVID-19 database*/
female_gwas_url,
male_gwas_url,
female_male_gwas_url,
outdir=/home/cheng.zhong.shan/my_shared_file_links/cheng.zhong.shan/F_vs_M_Covid19_Hosp,
forece=1,
label4female_gwas=F... |
a0abadc3e091503a7773d3d2beb9405d2054d5453908c90ca2daf97b5f28778c | SAS | 13,963 | 459 | %macro sc_scatter4gene(
dsd=,
dsd_headers=,
dsd_umap=,
gene=,
cell_type_var=cluster,
pheno_var=,
pheno_categories=,
grpvar4boxplot=,/*separate umap and boxplot by pheno_var and grpvar*/
samplewide=0,
sample_var=sample,
boxplot_width=1000,
boxplot_height=600,
umap_width=1000,
umap_height=500,
umap_lattice... |
bf49f66aa8a435209eb32ecc581cdc9f410399668b81e771a33d8f0c39b480b8 | SAS | 14,208 | 323 | %macro long2wide4multigrpsSameTypeVars(
/*Note: this macro is handy when there are multiple target numeric or characteric variables needs to be transposed to rowwide;
*Tranditional transpose procedure usually handle one type of variable to rowwide by other group variables;
*But this macro can abtain wide format tabl... |
6862e6ff085b3857dd261d972b81ac39b62de4189d7c6f4aa4e1ef472e344f4a | SAS | 14,213 | 489 | %macro get_macros_used_by_macro(/*This macro may run endlessly when the macro include its macro name without the Demo tag*/
macrorgx=.,/*No need to include \.sas, as the macro will only keep sas script having prefix matching with the macrorgx!*/
dir=%sysfunc(pathname(HOME))/Macros
~/shared/Macros
/home/zcheng/SAS-... |
e3df8f42ef215e9380e03b268226e815c55a8fc6e49a588ab250d0857c037ada | SAS | 14,490 | 466 | %macro InitEstHapFrq(
gen_pheno_sasdsd=,
/*The input sas dataset should be in the following format:
ID pheno cov1 snpA1 snpA2 snpB1 snpB2 snpC1 snpC2;
with two alleles represented by 0 and 1 and the order of allele1 and allele2 should be strictly put in the order of 0 and 1;
*/
Hapfrq_outdsd=Hapfrq,
/*Initially... |
b913b167b42599cc8bbd323cb9721e5e1a61afd5fe4dd21917be935510556ac8 | SAS | 14,815 | 391 |
*It is still better to have these raw SPredXcan association signals by tissue and HGI GWAS;
*To acomplish this, the raw SPredXcan output needs to be combined into a single file for making expected TWAS heatmap;
*Use my own Perl script to combine these files within linux docker image;
*H:\MetaXcan\MetaXcan\software... |
d97b99e70e400e7f98f70feefca9e0d74f98f35643cf251d9b32222df052bc64 | SAS | 15,051 | 496 |
/*The issue for this macro is that the two parameters startlinenum and endlinenum may
lead to the read of partial data for a specific feature, which means the records of the
feature may be splitted into two sections and included in two blocks*/
%macro ucsc_cell_mtx2iml(
/*This macro can import data from url, download... |
429ecb0d09247ce711fee3a870b8a293f1e7df24466109552b0a6b7cd2f88779 | SAS | 15,319 | 441 | %macro CaculateMulteQTLs_in_GTEx(
query_snps=rs17425819 rs7850484,
gene=JAK2,
genoexp_outdsd=genos_and_exps,/*output dataset name in long format for genotype and gene expression across different tissues*/
eQTLSumOutdsd=AssocSummary,
rgx4tissues=, /*optional regular expression to select specific tissues for haplotype as... |
6b9540bc92e0bbdc4521791a7dda5e2d04cf5707b76b4703d21dace4dd58b370 | SAS | 15,722 | 332 | %macro Long_format_muts2ProteinTrack(
/*See the demo code at the end of this macro for how to generate fake gtf and inptu data set based on ncbi gpff file;
Note: several important parameters can adjust the label on the top:
yoffset4max_drawmarkersontop and Yoffset4textlabels can be used to enlarge the top regions co... |
929229b57a0deb532833c920f8b7a9dd73e521d40479006675312edf90e87334 | SAS | 15,785 | 407 | %macro make_fake_axis4NegPosVal_by_grps(/*The macro will scale up or down positive or negative values and generate
yaxis macro labels with the original postive values; To keep using the original positive value but also to scale the ratio
between these positve and negative values, the macro variable NotChangePosVals ... |
01983b197e4d1899b08a457dc0ddcfbadf2bf40f7c03cc6d7668d23c12e67e4e | SAS | 16,000 | 523 | /* data a; */
/* input chr $ st end type $ grp $; */
/* cards; */
/* chr1 1 100 gene a */
/* chr1 10 20 exon a */
/* chr1 50 70 exon a */
/* chr1 200 800 gene b */
/* chr1 300 500 exon b */
/* chr1 600 700 exon b */
/* chr1 1100 3000 gene c */
/* chr1 1200 2000 exon c */
/* chr1 2200 2800 exon c */
/* chr1 ... |
ee6d5c41d919cf8241edcd3f60f89f133ad59f5af421aab6b11293779c2050dc | SAS | 16,435 | 507 | %macro sc_freq_boxplot(
/*Note: the macro also perform gene expression differential expression analysis!;*/
longformdsd,
cell_type_var= ,/*It will be used for lattice boxplot headernames*/
sample_grp_var= ,/*This will be used to generate sample level cell expression statistics*/
pheno_var= , /*Pheno var will be used a... |
c23b1f234120060a28389b92816da4913d0b6e7a98e7a4fea1bbc79d1bc93869 | SAS | 16,764 | 366 | %macro Long_format_GWAS2Wide(
longformat_GWAS=,/*Long format HGI GWAS with association signals in a union by same columns and different gwas dsd names;
Note: the input GWAS data should be in hg38 build if querying by genesymbol!*/
gwas_dsd_var=gwas,/*The gwas variable in the longformat_GWAS*/
filter4gwas_dsd=,/*Add ful... |
39d8d482dac3e13ba03d028dccdd3aa0d593401f8e9d50481993a2cac8dcbccf | SAS | 17,041 | 570 | %macro scASE_FMM_and_ORA_Analysis(
pathway_gene_dsd=base,/*a dataset containing genes that will be used to overlapped with ASE genes from the following celltype_level_dsd*/
pathway_gene_var=gene,/*variable name for genes in the pathway_gene_dsd*/
ASE_gene_var=gene,/*variable name for genes in the celltype_level_dsd*... |
8305723677027a4ae35ab46df8e95ec03489f591970d26f49f004dce83fe61e4 | SAS | 17,212 | 452 | * _\|/_
(o o)
+----oOO-{_}-OOo----------------------------------------------------------------------------+
: :
: Version... |
299aeeb40b3285a0cb1b703e9c7d8732f6b1ad4ac923f841ca699c56ecc26da8 | SAS | 17,445 | 530 | %macro Lattice_gscatter_over_bed_track0(/*Old macro without adding of gene annotation to tracks, which is for backup only*/
bed_dsd,/*Too many bed regions (>1000) for the gene track will slow down the macro dramatically*/
chr_var,
st_var,
end_var,
grp_var,
scatter_grp_var,
lattice_subgrp_var,
yval_var,
yaxis_label=Grou... |
34607c3dad382e6c00d36e7af04d4f070f3d08cb34e2347f685705ae4e5f2888 | SAS | 18,234 | 310 | %macro Gene_Local_Manhattan_With_GTF(
/*
Note: comparing to the macro SNP_Local_Manhattan_With_GTF, this macro has fewer parameters to control the final figure;
If possible, please use SNP_Local_Manhattan_With_GTF to draw gene level Manhattan by providing genomic range for a target gene;
As this macro use other s... |
f9db549909d9b3eba6a64712ead656f65a2ab8770474f232a873b7b3284ef42c | SAS | 19,022 | 517 | %macro clustergram4longformatdsd(
/*The limitation of clustergram4longformatdsd compared to clustergram4sas
is that the orders of two axes of final heatmap is sorted by varnames if not clustered,
as this macro will sort the long format data by rowname_var and colname_var, and then
tranpose it for cluster if either ... |
ecf4188e45f1d5fcad62790abcffb17a0c8320f1f4da8397b091cee52cb03d24 | SAS | 19,771 | 635 | %macro ucsc_cell_mtx2wideformatdsd(
/*This macro can import data from url, downloaded gz file, or even plain files*/
mtx_gzfile_or_url=matrix.mtx.gz,/*Important: Input fullpath or url for these 3 input files*/
feat_gzfile_or_url=features.tsv.gz,
barcode_gzfile_or_url=barcodes.tsv.gz,
dsdout4headers=header,
dsdout... |
71c37df0b44578457335f9821465ca5e2676fbb8b5e987d1dde36d0e99eb2a00 | SAS | 19,808 | 576 | %macro GetMultQTLs4GenesInGTEx(
/*Unlike the macro CaculateMulteQTLs_in_GTEx, this macro is helpful to get genotypes and gene expression for
multiple query SNPs and Genes at the same time; it output both long- and wide-form datasets for gene expression
corresponding to input genes, i.e., &genoexp_outdsd and &genoex... |
5b7a26680d71ef22d3f7d9d50a2df732f848fa141a19a99aad020d70abe2e312 | SAS | 20,709 | 765 | /*-----
* group: Data out
* purpose: Export SAS datasets and OUTPUT catalog entries as worksheets of an Excel file.<BR>This macro can write to _WEBOUT to deliver binary Excel worksheets from SAS/Intrnet applications
* notes: Requires Perl and modules XML::Simple, Spreadsheet::WriteExcel and Date::Calc<BR><i>Current ... |
8763c3857ecce77f4081a58b6cfd220794b2de21ed8e7b6cf8891ff39cc9621b | SAS | 20,973 | 564 | /*
UKBB 06.18.21 Hospitalized Positive vs. Non-Hospitalized Positive or Negative or Untested 1,343 / 262,886 Mixed F 47.88M 395 Summary Stats Annotated Grasp EBI GTeX eQLdb
UKBB 06.18.21 Hospitalized Positive vs. Non-Hospitalized Positive or Negative or Untested 1,917 / 221,174 Mixed M 47.45M 53... |
25713ca90f0ad1a622b876c2b6afca87e96a84a8e4014281e0c7103744919baa | SAS | 21,034 | 636 | %macro Lattice_gscatter_over_bed_track_(
bed_dsd,/*Too many bed regions (>1000) for the gene track will slow down the macro dramatically*/
chr_var,
st_var,
end_var,
grp_var,
scatter_grp_var,
lattice_subgrp_var,
yval_var,
yaxis_label=Group,
linethickness=20,
track_width=800,
track_height=400,
dist2st_and_end=0,
dotsize=... |
663351bfb5dfb9080b0c93ad90dce757b27d79d34b710a18fa48576e5b745188 | SAS | 21,737 | 549 | *https://sesug.org/proceedings/sesug_2024_SAAG/PresentationSummaries/Papers/151_Final_PDF.pdf;
*options mprint mlogic symbolgen;
filename M url "https://raw.githubusercontent.com/chengzhongshan/COVID19_GWAS_Analyzer/main/Macros/importallmacros_ue.sas";
%include M;
Filename M clear;
%importallmacros_ue(MacroDir=%s... |
30c2620934e75cad4b45ceefde92eab9800738333f1aa711319cc81bb9c91aff | SAS | 21,987 | 781 | %macro Boxplots4GenesInGTExV8ByGrps(
genes=MAP3K19 R3HDM1 CXCR4,
dsdout=exp,
bygrps=sex AA, /*by AA population and sex or either of them!*/
UseGeneratedDsd=0,
PreviousDsd=tgt, /*This is a fixed dsd used by the proc sgpanel*/
Lib4PreviousDsd=GTEx,
WhereFilters4Boxplot=%str(),/*such as cluster in ("Lung" "Spleen" ... |
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