stddata__2014_09_02 Samples Report
Overview
Introduction

The Broad GDAC mirrors data from the DCC on a daily basis. Although all data is mirrored, not every sample is ingested into Firehose. There are three main mechanisms that filter samples to ensure that only the most scientifically relevant samples make it into our standard data and analyses runs. These three mechanisms are redactions, replicate filtering, and blacklisting. This report summarizes the data that is ingested into Firehose, describes the three filtering mechanisms, lists those samples that are removed, and gives all available annotations from the DCC's Annotation Manager.

Summary

There were 161 redactions, 2943 replicate aliquots, 23 blacklisted aliquots, and 638 FFPE aliquots. The table below represents the sample counts for those samples that were ingested into firehose after filtering out redactions, replicates, and blacklisted data, and segregating FFPEs.

Table 1.  Get Full Table Summary of TCGA Tumor Data. Click on a tumor type to display a tumor type specific Samples Report.

Cohort BCR Clinical CN LowP Methylation mRNA mRNASeq miR miRSeq RPPA MAF
ACC 92 90 90 0 80 0 79 0 80 46 91
BLCA 412 222 309 112 367 0 310 0 310 127 130
BRCA 1097 1033 1053 19 1045 526 1058 0 1042 409 976
CESC 307 243 244 0 256 0 252 0 256 0 194
CHOL 36 0 0 0 0 0 0 0 0 0 0
COAD 460 442 438 69 445 153 443 0 406 331 154
COADREAD 631 613 600 104 610 222 606 0 549 461 223
DLBC 58 33 43 0 48 0 28 0 27 0 0
ESCA 185 143 184 32 185 0 125 0 175 0 0
GBM 613 582 571 0 420 540 160 565 0 214 290
HNSC 528 456 511 108 528 0 497 0 512 212 306
KICH 113 96 66 0 66 0 66 0 66 0 66
KIRC 537 520 527 0 535 72 531 0 515 454 417
KIRP 323 221 241 0 242 16 241 0 242 207 168
LAML 200 200 197 0 194 0 179 0 188 0 197
LGG 516 421 513 52 516 27 513 0 512 258 289
LIHC 377 222 266 0 291 0 268 0 268 0 202
LUAD 585 479 493 120 569 32 488 0 491 181 229
LUSC 504 422 490 0 492 154 489 0 467 195 178
MESO 87 36 57 0 87 0 36 0 26 0 0
OV 602 589 576 0 594 574 296 570 453 412 316
PAAD 185 118 102 0 146 0 124 0 129 106 91
PCPG 179 113 175 0 179 0 179 0 179 0 178
PRAD 499 352 420 115 425 0 419 0 421 164 261
READ 171 171 162 35 165 69 163 0 143 130 69
SARC 261 135 213 0 242 0 212 0 240 0 0
SKCM 470 398 384 118 458 0 382 0 415 204 343
STAD 443 353 372 107 386 0 274 0 372 264 221
TGCT 150 0 0 0 150 0 0 0 0 0 0
THCA 503 490 494 98 503 0 494 0 495 222 402
THYM 124 0 0 0 124 0 0 0 0 0 0
UCEC 560 498 540 106 547 54 538 0 534 200 248
UCS 57 57 56 0 57 0 57 0 56 0 57
UVM 80 0 47 0 80 0 0 0 0 0 0
Totals 11314 9135 9834 1091 10422 2217 8901 1135 9020 4336 6073
Results
Sample Heatmaps
ACC

Figure 1.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

BLCA

Figure 2.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

BRCA

Figure 3.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

CESC

Figure 4.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

CHOL

Figure 5.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

COAD

Figure 6.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

COADREAD

Figure 7.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

DLBC

Figure 8.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

ESCA

Figure 9.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

GBM

Figure 10.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

HNSC

Figure 11.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

KICH

Figure 12.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

KIRC

Figure 13.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

KIRP

Figure 14.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

LAML

Figure 15.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

LGG

Figure 16.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

LIHC

Figure 17.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

LUAD

Figure 18.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

LUSC

Figure 19.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

MESO

Figure 20.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

OV

Figure 21.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

PAAD

Figure 22.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

PCPG

Figure 23.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

PRAD

Figure 24.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

READ

Figure 25.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

SARC

Figure 26.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

SKCM

Figure 27.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

STAD

Figure 28.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

TGCT

Figure 29.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

THCA

Figure 30.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

THYM

Figure 31.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

UCEC

Figure 32.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

UCS

Figure 33.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

UVM

Figure 34.  Get High-res Image This figure depicts the distribution of available data on a per participant basis.

Filtered Samples

Redactions

Replicate Samples

Blacklisted Samples

FFPE Cases

FFPE Cases

Additional Annotations from the DCC's Annotations Manager

CenterNotifications

Notifications

Observations

Methods & Data
Redactions and Other Annotations

Annotation data was taken from theTCGA Data Portalusing the query string:

https://tcga-data.nci.nih.gov/annotations/resources/searchannotations/json?item=TCGA

Redaction information was generated by filtering for the annotationClassificationName "Redaction"

FFPE information was generated by filtering for "FFPE" in annotation note text

Additional FFPEs were garnered from clinical data

Remaining annotations were sorted into sections by annotationClassificationName

Preprocessors
mRNA Preprocessor

The mRNA preprocess median module chooses the matrix for the platform(Affymetrix HG U133, Affymetrix Exon Array and Agilent Gene Expression) with the largest number of samples.

mRNAseq Preprocessor

The mRNAseq preprocessor picks the "scaled_estimate" (RSEM) value from Illumina HiSeq/GA2 mRNAseq level_3 (v2) data set and makes the mRNAseq matrix with log2 transformed for the downstream analysis. If there are overlap samples between two different platforms, samples from illumina hiseq will be selected. The pipeline also creates the matrix with RPKM and log2 transform from HiSeq/GA2 mRNAseq level 3 (v1) data set.

miRseq Preprocessor

The miRseq preprocessor picks the "RPM" (reads per million miRNA precursor reads) from the Illumina HiSeq/GA miRseq Level_3 data set and makes the matrix with log2 transformed values.

Methylation Preprocessor

The methylation preprocessor filters methylation data for use in downstream pipelines. To learn more about this preprocessor, please visit the documentation.

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