# Realized\_relationship\_matrix

**URL:** <https://discuss.hail.is/t/realized-relationship-matrix/1800>\
**Category:** Hail Query & hailctl\
**Created:** [November 19, 2020, 8:45pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800 "2020-11-19T20:45:58Z")\
**Posts on this page:** 12\
**Page:** 1

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 19, 2020, 8:45pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/1 "2020-11-19T20:45:58Z")

</div>

Hello. I am very new to data science, and even more new to bioinformatic field.  
Now i will try to use realized\_relationship\_matrix  
So, first : import vcf file by / ds = hl.import\_vcf(‘75.vcf’)  
then : rrm = hl.realized\_relationship\_matrix(ds.GT)  
but the output is :

> FatalError Traceback (most recent call last)  
> in ()  
> ----\> 1 rrm = hl.realized\_relationship\_matrix(ds.GT)
> 
> in realized\_relationship\_matrix(call\_expr)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\methods\statgen.py in realized\_relationship\_matrix(call\_expr)  
> 1993  
> 1994 normalized\_gt = hl.or\_else((mt.\_\_gt - mt.\_\_mean\_gt) / mt.\_\_centered\_length, 0.0)  
> → 1995 bm = BlockMatrix.from\_entry\_expr(normalized\_gt)  
> 1996  
> 1997 return (bm.T @ bm) / (bm.n\_rows / bm.n\_cols)
> 
> in from\_entry\_expr(cls, entry\_expr, mean\_impute, center, normalize, axis, block\_size)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in from\_entry\_expr(cls, entry\_expr, mean\_impute, center, normalize, axis, block\_size)  
> 408 path = new\_temp\_file()  
> 409 cls.write\_from\_entry\_expr(entry\_expr, path, overwrite=False, mean\_impute=mean\_impute,  
> → 410 center=center, normalize=normalize, axis=axis, block\_size=block\_size)  
> 411 return cls.read(path)  
> 412
> 
> in write\_from\_entry\_expr(entry\_expr, path, overwrite, mean\_impute, center, normalize, axis, block\_size)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in write\_from\_entry\_expr(entry\_expr, path, overwrite, mean\_impute, center, normalize, axis, block\_size)  
> 716 else:  
> 717 field = Env.get\_uid()  
> → 718 mt.select\_entries(\*\*{field: entry\_expr}).\_write\_block\_matrix(path, overwrite, field, block\_size)  
> 719 else:  
> 720 mt = mt.select\_entries(\_\_x=entry\_expr).unfilter\_entries()
> 
> ~\Anaconda3\lib\site-packages\hail\matrixtable.py in \_write\_block\_matrix(self, path, overwrite, entry\_field, block\_size)  
> 4119 ‘overwrite’: overwrite,  
> 4120 ‘entryField’: entry\_field,  
> → 4121 ‘blockSize’: block\_size}))  
> 4122  
> 4123 def \_calculate\_new\_partitions(self, n\_partitions):
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in execute(self, ir, timed)  
> 96 raise HailUserError(message\_and\_trace) from None  
> 97  
> —\> 98 raise e
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in execute(self, ir, timed)  
> 72 # print(self.\_hail\_package.expr.ir.Pretty.apply(jir, True, -1))  
> 73 try:  
> —\> 74 result = json.loads(self.\_jhc.backend().executeJSON(jir))  
> 75 value = ir.typ.\_from\_json(result[‘value’])  
> 76 timings = result[‘timings’]
> 
> ~\Anaconda3\lib\site-packages\py4j\java\_gateway.py in **call** (self, \*args)  
> 1255 answer = self.gateway\_client.send\_command(command)  
> 1256 return\_value = get\_return\_value(  
> → 1257 answer, self.gateway\_client, self.target\_id, self.name)  
> 1258  
> 1259 for temp\_arg in temp\_args:
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in deco(\*args, \*\*kwargs)  
> 30 raise FatalError(‘%s\n\nJava stack trace:\n%s\n’  
> 31 ‘Hail version: %s\n’  
> —\> 32 ‘Error summary: %s’ % (deepest, full, hail. **version** , deepest), error\_id) from None  
> 33 except pyspark.sql.utils.CapturedException as e:  
> 34 raise FatalError(‘%s\n\nJava stack trace:\n%s\n’
> 
> FatalError: HailException: Invalid locus ‘chr13:32911888’ found. Contig ‘chr13’ is not in the reference genome ‘GRCh37’.
> 
> Java stack trace:  
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 43.0 failed 1 times, most recent failure: Lost task 0.0 in stage 43.0 (TID 146, localhost, executor driver): is.hail.utils.HailException: file:/C:/Users/m-a-b/75.vcf:offset 4730: error while parsing line  
> chr13 32911888 rs1801406 A G 100 PASS DP=556;clinvar=1|benign,1|benign,1|benign,1|benign,1|benign,1|benign;cosmic=1|COSM4415775,1|COSM4415776;GMAF=G|0.2668;AA=A;AF1000G=0.266773;phyloP=-0.265;CSQT=1|BRCA2|NM\_000059.3|synonymous\_variant GT:GQ:AD:DP:VF:NL:SB:NC 0/1:100:278,278:556:0.500:20:-100.0000:0.0000
> 
> at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:15)  
> at is.hail.utils.package$.fatal(package.scala:77)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1745)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1734)  
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464)  
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)  
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1219)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1218)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:232)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:230)  
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)  
> at org.apache.spark.scheduler.Task.run(Task.scala:121)  
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)  
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)  
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)  
> at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)  
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)  
> at java.lang.Thread.run(Unknown Source)  
> Caused by: is.hail.utils.HailException: Invalid locus ‘chr13:32911888’ found. Contig ‘chr13’ is not in the reference genome ‘GRCh37’.  
> at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:11)  
> at is.hail.utils.package$.fatal(package.scala:77)  
> at is.hail.variant.ReferenceGenome.checkLocus(ReferenceGenome.scala:206)  
> at is.hail.io.vcf.VCFLine$$anonfun$parseAddVariant$2.apply(LoadVCF.scala:358)  
> at is.hail.io.vcf.VCFLine$$anonfun$parseAddVariant$2.apply(LoadVCF.scala:358)  
> at scala.Option.foreach(Option.scala:257)  
> at is.hail.io.vcf.VCFLine.parseAddVariant(LoadVCF.scala:358)  
> at is.hail.io.vcf.LoadVCF$.parseLine(LoadVCF.scala:1300)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1741)  
> … 16 more
> 
> Driver stacktrace:  
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)  
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)  
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)  
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)  
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)  
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)  
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)  
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)  
> at scala.Option.foreach(Option.scala:257)  
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)  
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)  
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)  
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)  
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)  
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)  
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)  
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)  
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)  
> at is.hail.sparkextras.ContextRDD.crunJobWithIndex(ContextRDD.scala:228)  
> at is.hail.rvd.RVD$.getKeyInfo(RVD.scala:1218)  
> at is.hail.rvd.RVD$.makeCoercer(RVD.scala:1293)  
> at is.hail.expr.ir.GenericTableValue.getRVDCoercer(GenericTableValue.scala:162)  
> at is.hail.expr.ir.GenericTableValue.toTableValue(GenericTableValue.scala:188)  
> at is.hail.io.vcf.MatrixVCFReader.apply(LoadVCF.scala:1773)  
> at is.hail.expr.ir.TableRead.execute(TableIR.scala:1100)  
> at is.hail.expr.ir.TableMapRows.execute(TableIR.scala:1845)  
> at is.hail.expr.ir.TableFilter.execute(TableIR.scala:1279)  
> at is.hail.expr.ir.TableMapRows.execute(TableIR.scala:1845)  
> at is.hail.expr.ir.Interpret$.run(Interpret.scala:831)  
> at is.hail.expr.ir.Interpret$.alreadyLowered(Interpret.scala:53)  
> at is.hail.expr.ir.InterpretNonCompilable$.interpretAndCoerce$1(InterpretNonCompilable.scala:16)  
> at is.hail.expr.ir.InterpretNonCompilable$.is$hail$expr$ir$InterpretNonCompilable$$rewrite$1(InterpretNonCompilable.scala:53)  
> at is.hail.expr.ir.InterpretNonCompilable$.apply(InterpretNonCompilable.scala:58)  
> at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.transform(LoweringPass.scala:67)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)  
> at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:15)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:13)  
> at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)  
> at is.hail.expr.ir.lowering.LoweringPass$class.apply(LoweringPass.scala:13)  
> at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.apply(LoweringPass.scala:62)  
> at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:14)  
> at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:12)  
> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)  
> at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)  
> at is.hail.expr.ir.lowering.LoweringPipeline.apply(LoweringPipeline.scala:12)  
> at is.hail.expr.ir.CompileAndEvaluate$.\_apply(CompileAndEvaluate.scala:28)  
> at is.hail.backend.spark.SparkBackend.is$hail$backend$spark$SparkBackend$$\_execute(SparkBackend.scala:354)  
> at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:338)  
> at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:335)  
> at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:25)  
> at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:23)  
> at is.hail.utils.package$.using(package.scala:618)  
> at is.hail.annotations.Region$.scoped(Region.scala:18)  
> at is.hail.expr.ir.ExecuteContext$.scoped(ExecuteContext.scala:23)  
> at is.hail.backend.spark.SparkBackend.withExecuteContext(SparkBackend.scala:247)  
> at is.hail.backend.spark.SparkBackend.execute(SparkBackend.scala:335)  
> at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:379)  
> at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:377)  
> at is.hail.utils.ExecutionTimer$.time(ExecutionTimer.scala:52)  
> at is.hail.backend.spark.SparkBackend.executeJSON(SparkBackend.scala:377)  
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)  
> at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)  
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)  
> at java.lang.reflect.Method.invoke(Unknown Source)  
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)  
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)  
> at py4j.Gateway.invoke(Gateway.java:282)  
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)  
> at py4j.commands.CallCommand.execute(CallCommand.java:79)  
> at py4j.GatewayConnection.run(GatewayConnection.java:238)  
> at java.lang.Thread.run(Unknown Source)
> 
> is.hail.utils.HailException: file:/C:/Users/m-a-b/75.vcf:offset 4730: error while parsing line  
> chr13 32911888 rs1801406 A G 100 PASS DP=556;clinvar=1|benign,1|benign,1|benign,1|benign,1|benign,1|benign;cosmic=1|COSM4415775,1|COSM4415776;GMAF=G|0.2668;AA=A;AF1000G=0.266773;phyloP=-0.265;CSQT=1|BRCA2|NM\_000059.3|synonymous\_variant GT:GQ:AD:DP:VF:NL:SB:NC 0/1:100:278,278:556:0.500:20:-100.0000:0.0000
> 
> at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:15)  
> at is.hail.utils.package$.fatal(package.scala:77)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1745)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1734)  
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464)  
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)  
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1219)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1218)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:232)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:230)  
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)  
> at org.apache.spark.scheduler.Task.run(Task.scala:121)  
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)  
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)  
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)  
> at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)  
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)  
> at java.lang.Thread.run(Unknown Source)
> 
> is.hail.utils.HailException: Invalid locus ‘chr13:32911888’ found. Contig ‘chr13’ is not in the reference genome ‘GRCh37’.  
> at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:11)  
> at is.hail.utils.package$.fatal(package.scala:77)  
> at is.hail.variant.ReferenceGenome.checkLocus(ReferenceGenome.scala:206)  
> at is.hail.io.vcf.VCFLine$$anonfun$parseAddVariant$2.apply(LoadVCF.scala:358)  
> at is.hail.io.vcf.VCFLine$$anonfun$parseAddVariant$2.apply(LoadVCF.scala:358)  
> at scala.Option.foreach(Option.scala:257)  
> at is.hail.io.vcf.VCFLine.parseAddVariant(LoadVCF.scala:358)  
> at is.hail.io.vcf.LoadVCF$.parseLine(LoadVCF.scala:1300)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1741)  
> at is.hail.io.vcf.MatrixVCFReader$$anonfun$21$$anonfun$apply$10$$anonfun$apply$11.apply(LoadVCF.scala:1734)  
> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:464)  
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)  
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1219)  
> at is.hail.rvd.RVD$$anonfun$33.apply(RVD.scala:1218)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:232)  
> at is.hail.sparkextras.ContextRDD$$anonfun$crunJobWithIndex$1.apply(ContextRDD.scala:230)  
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)  
> at org.apache.spark.scheduler.Task.run(Task.scala:121)  
> at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:403)  
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)  
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:409)  
> at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)  
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)  
> at java.lang.Thread.run(Unknown Source)
> 
> Hail version: 0.2.60-de1845e1c2f6  
> Error summary: HailException: Invalid locus ‘chr13:32911888’ found. Contig ‘chr13’ is not in the reference genome ‘GRCh37’.

so what is the problem ? and how can i solve it?  
Thank you a lot

---

<div class="post-metadata">

**Author:** ![johnc1231](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/johnc1231/32/286_2.png) [@johnc1231](https://discuss.hail.is/u/johnc1231)\
**Post date:** [November 19, 2020, 9:08pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/2 "2020-11-19T21:08:56Z")

</div>

> [@Arwa](#):
>
> Error summary: HailException: Invalid locus ‘chr13:32911888’ found. Contig ‘chr13’ is not in the reference genome ‘GRCh37’.

This is the relevant bit. When you import a vcf, you have to specify a reference genome. By default, we guess `GRCh37`. In `GRCh37` vcfs, the contig is supposed to just be a number. So for chomrosome 1 the line of the vcf would start with a “1”. In `GRCh38` VCFs, it instead starts like “chr1”.

So either you have a GRCh38 VCF, and you have to specify that when you import your vcf (see `reference_genome` here: [Hail | Import / Export](https://hail.is/docs/0.2/methods/impex.html#hail.methods.import_vcf)), or you have a malformed GRCh37 VCF, and you’ll have to use the `contig_recoding` argument to `import_vcf` to fix it (see second example in `import_vcf` docs).

---

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 19, 2020, 9:22pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/3 "2020-11-19T21:22:27Z")

</div>

> [@johnc1231](#):
>
> This is the relevant bit. When you import a vcf, you have to specify a reference genome. By default, we guess `GRCh37` . In `GRCh37` vcfs, the contig is supposed to just be a number. So for chomrosome 1 the line of the vcf would start with a “1”. In `GRCh38` VCFs, it instead starts like “chr1”.
> 
> So either you have a GRCh38 VCF, and you have to specify that when you import your vcf (see `reference_genome` here: [Hail | Import / Export](https://hail.is/docs/0.2/methods/impex.html#hail.methods.import_vcf)), or you have a malformed GRCh37 VCF, and you’ll have to use the `contig_recoding` argument to `import_vcf` to fix it (see second example in `import_vcf` docs).

thank you. but i didn’t understand how i know that CRCh37 or CRCh38 ?  
also if i replaced my old import by this import :  
recode = {f"{i}“:f"chr{i}” for i in (list(range(1, 23)) + [‘X’, ‘Y’])}  
ds = hl.import\_vcf(‘75.vcf’, reference\_genome=‘GRCh38’, contig\_recoding=recode)

and i run the code , this error will appear to me :

> FatalError Traceback (most recent call last)  
> in ()  
> ----\> 1 rrm = hl.realized\_relationship\_matrix(ds.GT)

```
<decorator-gen-1719> in realized_relationship_matrix(call_expr)

~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(__original_func, *args, **kwargs)
    612 def wrapper(__original_func, *args, **kwargs):
    613 args_, kwargs_ = check_all(__original_func, args, kwargs, checkers, is_method=is_method)
--> 614 return __original_func(*args_, **kwargs_)
    615 
    616 return wrapper

~\Anaconda3\lib\site-packages\hail\methods\statgen.py in realized_relationship_matrix(call_expr)
   1993 
   1994 normalized_gt = hl.or_else((mt. __gt - mt.__ mean_gt) / mt.__centered_length, 0.0)
-> 1995 bm = BlockMatrix.from_entry_expr(normalized_gt)
   1996 
   1997 return (bm.T @ bm) / (bm.n_rows / bm.n_cols)

<decorator-gen-1449> in from_entry_expr(cls, entry_expr, mean_impute, center, normalize, axis, block_size)

~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(__original_func, *args, **kwargs)
    612 def wrapper(__original_func, *args, **kwargs):
    613 args_, kwargs_ = check_all(__original_func, args, kwargs, checkers, is_method=is_method)
--> 614 return __original_func(*args_, **kwargs_)
    615 
    616 return wrapper

~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in from_entry_expr(cls, entry_expr, mean_impute, center, normalize, axis, block_size)
    408 path = new_temp_file()
    409 cls.write_from_entry_expr(entry_expr, path, overwrite=False, mean_impute=mean_impute,
--> 410 center=center, normalize=normalize, axis=axis, block_size=block_size)
    411 return cls.read(path)
    412 

<decorator-gen-1461> in write_from_entry_expr(entry_expr, path, overwrite, mean_impute, center, normalize, axis, block_size)

~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(__original_func, *args, **kwargs)
    612 def wrapper(__original_func, *args, **kwargs):
    613 args_, kwargs_ = check_all(__original_func, args, kwargs, checkers, is_method=is_method)
--> 614 return __original_func(*args_, **kwargs_)
    615 
    616 return wrapper

~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in write_from_entry_expr(entry_expr, path, overwrite, mean_impute, center, normalize, axis, block_size)
    716 else:
    717 field = Env.get_uid()
--> 718 mt.select_entries(**{field: entry_expr})._write_block_matrix(path, overwrite, field, block_size)
    719 else:
    720 mt = mt.select_entries(__x=entry_expr).unfilter_entries()

~\Anaconda3\lib\site-packages\hail\matrixtable.py in _write_block_matrix(self, path, overwrite, entry_field, block_size)
   4119 'overwrite': overwrite,
   4120 'entryField': entry_field,
-> 4121 'blockSize': block_size}))
   4122 
   4123 def _calculate_new_partitions(self, n_partitions):

~\Anaconda3\lib\site-packages\hail\backend\py4j_backend.py in execute(self, ir, timed)
     96 raise HailUserError(message_and_trace) from None
     97 
---> 98 raise e

~\Anaconda3\lib\site-packages\hail\backend\py4j_backend.py in execute(self, ir, timed)
     72 # print(self._hail_package.expr.ir.Pretty.apply(jir, True, -1))
     73 try:
---> 74 result = json.loads(self._jhc.backend().executeJSON(jir))
     75 value = ir.typ._from_json(result['value'])
     76 timings = result['timings']

~\Anaconda3\lib\site-packages\py4j\java_gateway.py in __call__ (self, *args)
   1255 answer = self.gateway_client.send_command(command)
   1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
   1258 
   1259 for temp_arg in temp_args:

~\Anaconda3\lib\site-packages\hail\backend\py4j_backend.py in deco(*args, **kwargs)
     30 raise FatalError('%s\n\nJava stack trace:\n%s\n'
     31 'Hail version: %s\n'
---> 32 'Error summary: %s' % (deepest, full, hail. __version__ , deepest), error_id) from None
     33 except pyspark.sql.utils.CapturedException as e:
     34 raise FatalError('%s\n\nJava stack trace:\n%s\n'

FatalError: HailException: block matrix must have at least one row

Java stack trace:
is.hail.utils.HailException: block matrix must have at least one row
	at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:11)
	at is.hail.utils.package$.fatal(package.scala:77)
	at is.hail.linalg.GridPartitioner.<init>(GridPartitioner.scala:19)
	at is.hail.expr.ir.functions.MatrixWriteBlockMatrix.execute(MatrixWriteBlockMatrix.scala:44)
	at is.hail.expr.ir.functions.WrappedMatrixToValueFunction.execute(RelationalFunctions.scala:88)
	at is.hail.expr.ir.Interpret$.run(Interpret.scala:831)
	at is.hail.expr.ir.Interpret$.alreadyLowered(Interpret.scala:53)
	at is.hail.expr.ir.InterpretNonCompilable$.interpretAndCoerce$1(InterpretNonCompilable.scala:16)
	at is.hail.expr.ir.InterpretNonCompilable$.is$hail$expr$ir$InterpretNonCompilable$$rewrite$1(InterpretNonCompilable.scala:53)
	at is.hail.expr.ir.InterpretNonCompilable$.apply(InterpretNonCompilable.scala:58)
	at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.transform(LoweringPass.scala:67)
	at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)
	at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)
	at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)
	at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:15)
	at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:13)
	at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)
	at is.hail.expr.ir.lowering.LoweringPass$class.apply(LoweringPass.scala:13)
	at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.apply(LoweringPass.scala:62)
	at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:14)
	at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:12)
	at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
	at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
	at is.hail.expr.ir.lowering.LoweringPipeline.apply(LoweringPipeline.scala:12)
	at is.hail.expr.ir.CompileAndEvaluate$._apply(CompileAndEvaluate.scala:28)
	at is.hail.backend.spark.SparkBackend.is$hail$backend$spark$SparkBackend$$_execute(SparkBackend.scala:354)
	at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:338)
	at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:335)
	at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:25)
	at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:23)
	at is.hail.utils.package$.using(package.scala:618)
	at is.hail.annotations.Region$.scoped(Region.scala:18)
	at is.hail.expr.ir.ExecuteContext$.scoped(ExecuteContext.scala:23)
	at is.hail.backend.spark.SparkBackend.withExecuteContext(SparkBackend.scala:247)
	at is.hail.backend.spark.SparkBackend.execute(SparkBackend.scala:335)
	at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:379)
	at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:377)
	at is.hail.utils.ExecutionTimer$.time(ExecutionTimer.scala:52)
	at is.hail.backend.spark.SparkBackend.executeJSON(SparkBackend.scala:377)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
	at java.lang.reflect.Method.invoke(Unknown Source)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:282)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:238)
	at java.lang.Thread.run(Unknown Source)

Hail version: 0.2.60-de1845e1c2f6
Error summary: HailException: block matrix must have at least one row

```

so what the problem now? and how can i solve it ☹  
Thank you again very much.

---

<div class="post-metadata">

**Author:** ![johnc1231](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/johnc1231/32/286_2.png) [@johnc1231](https://discuss.hail.is/u/johnc1231)\
**Post date:** [November 19, 2020, 9:35pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/4 "2020-11-19T21:35:13Z")

</div>

You shouldn’t do both the contig recoding and the reference genome change. It’s one or the other. Your VCF file should tell you what fasta file was used to align, which might help determine which reference genome you have. If it’s not clear, you should ask whoever you got the VCF from whether it’s GRCh37 or 38. I’d guess 38 based on the contig names but we see a fair number of GRCh37 VCFs that break the rules.

The error you’re getting suggest there are no rows in the VCF. Do `ds.count()` and check if it’s empty.

---

<div class="post-metadata">

**Author:** ![danking](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/danking/32/43_2.png) [@danking](https://discuss.hail.is/u/danking)\
**Post date:** [November 19, 2020, 9:35pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/5 "2020-11-19T21:35:30Z")

</div>

We can’t tell you what reference your dataset was aligned to. You need to ask whomever gave you `75.vcf` how that file was created.

It sounds like your dataset is empty. What does

```auto
print(ds.count())
ds.show()

```

Print?

---

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 19, 2020, 9:58pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/6 "2020-11-19T21:58:31Z")

</div>

This is not my data. It’s from internet but I train using them

about your question:  
yes it’s print. if I wrote a VCF with GRCh38

> ```
> > |locus|alleles|
> > |locus<GRCh38>|array<str>|
> > |chr13:32911888|["A","G"]|
> > |chr13:32912299|["T","C"]|
> > |chr13:32913055|["A","G"]|
> > |chr13:32915005|["G","C"]|
> > |chr13:32929232|["A","G"]|
> > |chr13:32929387|["T","C"]|
> > |chr13:32936646|["T","C"]|
> > |chr13:32953388|["T","C"]|
> > |chr17:41197659|["G","C"]|
> > |chr17:41201130|["A","G"]|
> 
> ```

but if I import with GRCh37 = the error message will occur!  
how can I solve it please ☹

---

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 19, 2020, 10:02pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/8 "2020-11-19T22:02:25Z")

</div>

Thank you very much. I will ask my doctor about reference genome.  
and it’s print!  
I really don’t understand what the problem!

---

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 20, 2020, 8:47pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/9 "2020-11-20T20:47:40Z")

</div>

Also , I want to make sure : this method realized relationship matrix is convert vcf file to genotype matrix  
so, it’s have matrix about samples and genotype ???  
If yes , how can i solve this problem

> FatalError Traceback (most recent call last)  
> in ()  
> ----\> 1 rrm = hl.realized\_relationship\_matrix(ds.GT)
> 
> in realized\_relationship\_matrix(call\_expr)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\methods\statgen.py in realized\_relationship\_matrix(call\_expr)  
> 1993  
> 1994 normalized\_gt = hl.or\_else((mt.\_\_gt - mt.\_\_mean\_gt) / mt.\_\_centered\_length, 0.0)  
> → 1995 bm = BlockMatrix.from\_entry\_expr(normalized\_gt)  
> 1996  
> 1997 return (bm.T @ bm) / (bm.n\_rows / bm.n\_cols)
> 
> in from\_entry\_expr(cls, entry\_expr, mean\_impute, center, normalize, axis, block\_size)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in from\_entry\_expr(cls, entry\_expr, mean\_impute, center, normalize, axis, block\_size)  
> 408 path = new\_temp\_file()  
> 409 cls.write\_from\_entry\_expr(entry\_expr, path, overwrite=False, mean\_impute=mean\_impute,  
> → 410 center=center, normalize=normalize, axis=axis, block\_size=block\_size)  
> 411 return cls.read(path)  
> 412
> 
> in write\_from\_entry\_expr(entry\_expr, path, overwrite, mean\_impute, center, normalize, axis, block\_size)
> 
> ~\Anaconda3\lib\site-packages\hail\typecheck\check.py in wrapper(\_\_original\_func, \*args, \*\*kwargs)  
> 612 def wrapper(_original\_func, \*args, \*\*kwargs):  
> 613 args, kwargs_ = check\_all(\_\_original\_func, args, kwargs, checkers, is\_method=is\_method)  
> → 614 return _original\_func(\*args, \*\*kwargs_)  
> 615  
> 616 return wrapper
> 
> ~\Anaconda3\lib\site-packages\hail\linalg\blockmatrix.py in write\_from\_entry\_expr(entry\_expr, path, overwrite, mean\_impute, center, normalize, axis, block\_size)  
> 716 else:  
> 717 field = Env.get\_uid()  
> → 718 mt.select\_entries(\*\*{field: entry\_expr}).\_write\_block\_matrix(path, overwrite, field, block\_size)  
> 719 else:  
> 720 mt = mt.select\_entries(\_\_x=entry\_expr).unfilter\_entries()
> 
> ~\Anaconda3\lib\site-packages\hail\matrixtable.py in \_write\_block\_matrix(self, path, overwrite, entry\_field, block\_size)  
> 4119 ‘overwrite’: overwrite,  
> 4120 ‘entryField’: entry\_field,  
> → 4121 ‘blockSize’: block\_size}))  
> 4122  
> 4123 def \_calculate\_new\_partitions(self, n\_partitions):
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in execute(self, ir, timed)  
> 96 raise HailUserError(message\_and\_trace) from None  
> 97  
> —\> 98 raise e
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in execute(self, ir, timed)  
> 72 # print(self.\_hail\_package.expr.ir.Pretty.apply(jir, True, -1))  
> 73 try:  
> —\> 74 result = json.loads(self.\_jhc.backend().executeJSON(jir))  
> 75 value = ir.typ.\_from\_json(result[‘value’])  
> 76 timings = result[‘timings’]
> 
> ~\Anaconda3\lib\site-packages\py4j\java\_gateway.py in **call** (self, \*args)  
> 1255 answer = self.gateway\_client.send\_command(command)  
> 1256 return\_value = get\_return\_value(  
> → 1257 answer, self.gateway\_client, self.target\_id, self.name)  
> 1258  
> 1259 for temp\_arg in temp\_args:
> 
> ~\Anaconda3\lib\site-packages\hail\backend\py4j\_backend.py in deco(\*args, \*\*kwargs)  
> 30 raise FatalError(‘%s\n\nJava stack trace:\n%s\n’  
> 31 ‘Hail version: %s\n’  
> —\> 32 ‘Error summary: %s’ % (deepest, full, hail. **version** , deepest), error\_id) from None  
> 33 except pyspark.sql.utils.CapturedException as e:  
> 34 raise FatalError(‘%s\n\nJava stack trace:\n%s\n’
> 
> FatalError: HailException: block matrix must have at least one row
> 
> Java stack trace:  
> is.hail.utils.HailException: block matrix must have at least one row  
> at is.hail.utils.ErrorHandling$class.fatal(ErrorHandling.scala:11)  
> at is.hail.utils.package$.fatal(package.scala:77)  
> at is.hail.linalg.GridPartitioner.(GridPartitioner.scala:19)  
> at is.hail.expr.ir.functions.MatrixWriteBlockMatrix.execute(MatrixWriteBlockMatrix.scala:44)  
> at is.hail.expr.ir.functions.WrappedMatrixToValueFunction.execute(RelationalFunctions.scala:88)  
> at is.hail.expr.ir.Interpret$.run(Interpret.scala:831)  
> at is.hail.expr.ir.Interpret$.alreadyLowered(Interpret.scala:53)  
> at is.hail.expr.ir.InterpretNonCompilable$.interpretAndCoerce$1(InterpretNonCompilable.scala:16)  
> at is.hail.expr.ir.InterpretNonCompilable$.is$hail$expr$ir$InterpretNonCompilable$$rewrite$1(InterpretNonCompilable.scala:53)  
> at is.hail.expr.ir.InterpretNonCompilable$.apply(InterpretNonCompilable.scala:58)  
> at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.transform(LoweringPass.scala:67)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3$$anonfun$1.apply(LoweringPass.scala:15)  
> at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:15)  
> at is.hail.expr.ir.lowering.LoweringPass$$anonfun$apply$3.apply(LoweringPass.scala:13)  
> at is.hail.utils.ExecutionTimer.time(ExecutionTimer.scala:81)  
> at is.hail.expr.ir.lowering.LoweringPass$class.apply(LoweringPass.scala:13)  
> at is.hail.expr.ir.lowering.InterpretNonCompilablePass$.apply(LoweringPass.scala:62)  
> at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:14)  
> at is.hail.expr.ir.lowering.LoweringPipeline$$anonfun$apply$1.apply(LoweringPipeline.scala:12)  
> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)  
> at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)  
> at is.hail.expr.ir.lowering.LoweringPipeline.apply(LoweringPipeline.scala:12)  
> at is.hail.expr.ir.CompileAndEvaluate$.\_apply(CompileAndEvaluate.scala:28)  
> at is.hail.backend.spark.SparkBackend.is$hail$backend$spark$SparkBackend$$\_execute(SparkBackend.scala:354)  
> at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:338)  
> at is.hail.backend.spark.SparkBackend$$anonfun$execute$1.apply(SparkBackend.scala:335)  
> at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:25)  
> at is.hail.expr.ir.ExecuteContext$$anonfun$scoped$1.apply(ExecuteContext.scala:23)  
> at is.hail.utils.package$.using(package.scala:618)  
> at is.hail.annotations.Region$.scoped(Region.scala:18)  
> at is.hail.expr.ir.ExecuteContext$.scoped(ExecuteContext.scala:23)  
> at is.hail.backend.spark.SparkBackend.withExecuteContext(SparkBackend.scala:247)  
> at is.hail.backend.spark.SparkBackend.execute(SparkBackend.scala:335)  
> at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:379)  
> at is.hail.backend.spark.SparkBackend$$anonfun$7.apply(SparkBackend.scala:377)  
> at is.hail.utils.ExecutionTimer$.time(ExecutionTimer.scala:52)  
> at is.hail.backend.spark.SparkBackend.executeJSON(SparkBackend.scala:377)  
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)  
> at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)  
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)  
> at java.lang.reflect.Method.invoke(Unknown Source)  
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)  
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)  
> at py4j.Gateway.invoke(Gateway.java:282)  
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)  
> at py4j.commands.CallCommand.execute(CallCommand.java:79)  
> at py4j.GatewayConnection.run(GatewayConnection.java:238)  
> at java.lang.Thread.run(Unknown Source)
> 
> Hail version: 0.2.60-de1845e1c2f6  
> Error summary: HailException: block matrix must have at least one row

If no, I want to create matrix that have only samples and genotype … how I can do it ?  
Thanks …

---

<div class="post-metadata">

**Author:** ![danking](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/danking/32/43_2.png) [@danking](https://discuss.hail.is/u/danking)\
**Post date:** [November 20, 2020, 11:37pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/10 "2020-11-20T23:37:46Z")

</div>

The realized relationship matrix is a sample-sample relationship matrix, it is not a matrix of genotypes.

I strongly suspect your VCF file has no samples (and, therefore, no genotypes). What is the output of

```auto
mt.count()

```

---

<div class="post-metadata">

**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 20, 2020, 11:45pm UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/11 "2020-11-20T23:45:40Z")

</div>

So, what is the output from it the realized relationship matrix?  
I didn’t find the output when I want to understand Can I see example of results?

- 

This is the code of import and to print 🙂

> recode = {f"{i}“:f"chr{i}” for i in (list(range(1, 23)) + [‘X’, ‘Y’])}  
> ds = hl.import\_vcf(‘75.vcf’, reference\_genome=‘GRCh38’, contig\_recoding=recode)  
> ds.count()

And this is the result :

> 2020-11-21 02:41:51 Hail: INFO: Coerced sorted dataset  
> Out[30]:  
> (23, 1)

---

<div class="post-metadata">

**Author:** ![danking](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/danking/32/43_2.png) [@danking](https://discuss.hail.is/u/danking)\
**Post date:** [November 21, 2020, 12:10am UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/12 "2020-11-21T00:10:20Z")

</div>

Your VCF file only has 1 sample, so it doesn’t make sense to create a Realized Relationship Matrix. A realized relationship matrix is a matrix that relates the samples of a dataset to one another. You only have one sample, so that matrix would be just one number: the number 1.

If you want to look at the 23 genotypes in your VCF you can run:

```auto
mt.show()

```

Hail is used to analyze large datasets. Hail is not very helpful for looking at a single genome. You may enjoy this book: [https://www.amazon.com/Exploring-Personal-Genomics-Joel-Dudley/dp/0199644497](https://www.amazon.com/Exploring-Personal-Genomics-Joel-Dudley/dp/0199644497)

---

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**Author:** ![Arwa](https://avatars.discourse-cdn.com/v4/letter/a/ccd318/32.png) [@Arwa](https://discuss.hail.is/u/Arwa)\
**Post date:** [November 21, 2020, 12:24am UTC](https://discuss.hail.is/t/realized-relationship-matrix/1800/13 "2020-11-21T00:24:19Z")

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Thank you, ❤  
I understand now!  
But I have multiple vcf files …  
I need to create a ( genotype matrix) matrix that the rows related to which patients and the columns GT ( like 0/1 … ) for each variants  
to make a machine learning on it  
how I can do it???