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Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples.
You can learn more about ARCHS4 and its pipeline here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| Heart tissue |
GSM5982086 GSM5982087
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GSM5982068 GSM5982069
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GSM5982032 GSM5982033
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GSM5982040 GSM5982041
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GSM5982056 GSM5982057
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GSM5982122 GSM5982123
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GSM5982076 GSM5982077
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GSM5982118 GSM5982119
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GSM5982110 GSM5982111
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GSM5982116 GSM5982117
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GSM5982074 GSM5982075
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GSM5982016 GSM5982017
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GSM5982130 GSM5982131
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GSM5982106 GSM5982107
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GSM5982046 GSM5982047
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GSM5982064 GSM5982065
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GSM5982018 GSM5982019
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GSM5982104 GSM5982105
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GSM5982124 GSM5982125
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GSM5982048 GSM5982049
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GSM5982054 GSM5982055
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GSM5982060 GSM5982061
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GSM5982120 GSM5982121
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GSM5982108 GSM5982109
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GSM5982092 GSM5982093
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GSM5982028 GSM5982029
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GSM5982020 GSM5982021
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GSM5982126 GSM5982127
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GSM5982088 GSM5982089
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GSM5982080 GSM5982081
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GSM5982022 GSM5982023
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GSM5982062 GSM5982063
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GSM5982024 GSM5982025
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GSM5982096 GSM5982097
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GSM5982034 GSM5982035
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GSM5982112 GSM5982113
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GSM5982036 GSM5982037
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GSM5982058 GSM5982059
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GSM5982044 GSM5982045
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GSM5982100 GSM5982101
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GSM5982084 GSM5982085
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GSM5982052 GSM5982053
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GSM5982102 GSM5982103
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GSM5982072 GSM5982073
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GSM5982042 GSM5982043
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GSM5982128 GSM5982129
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GSM5982090 GSM5982091
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GSM5982098 GSM5982099
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GSM5982038 GSM5982039
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GSM5982082 GSM5982083
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GSM5982066 GSM5982067
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GSM5982026 GSM5982027
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GSM5982078 GSM5982079
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GSM5982094 GSM5982095
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GSM5982030 GSM5982031
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GSM5982050 GSM5982051
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GSM5982114 GSM5982115
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GSM5982070 GSM5982071
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| Kidney tissue |
GSM5982202 GSM5982203
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GSM5982184 GSM5982185
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GSM5982148 GSM5982149
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GSM5982156 GSM5982157
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GSM5982172 GSM5982173
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GSM5982238 GSM5982239
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GSM5982192 GSM5982193
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GSM5982234 GSM5982235
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GSM5982226 GSM5982227
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GSM5982232 GSM5982233
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GSM5982190 GSM5982191
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GSM5982132 GSM5982133
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GSM5982246 GSM5982247
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GSM5982222 GSM5982223
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GSM5982162 GSM5982163
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GSM5982180 GSM5982181
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GSM5982134 GSM5982135
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GSM5982220 GSM5982221
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GSM5982240 GSM5982241
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GSM5982164 GSM5982165
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GSM5982170 GSM5982171
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GSM5982176 GSM5982177
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GSM5982236 GSM5982237
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GSM5982224 GSM5982225
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GSM5982208 GSM5982209
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GSM5982144 GSM5982145
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GSM5982136 GSM5982137
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GSM5982242 GSM5982243
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GSM5982204 GSM5982205
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GSM5982196 GSM5982197
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GSM5982138 GSM5982139
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GSM5982178 GSM5982179
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GSM5982140 GSM5982141
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GSM5982212 GSM5982213
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GSM5982150 GSM5982151
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GSM5982228 GSM5982229
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GSM5982152 GSM5982153
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GSM5982174 GSM5982175
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GSM5982160 GSM5982161
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GSM5982216 GSM5982217
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GSM5982200 GSM5982201
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GSM5982168 GSM5982169
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GSM5982218 GSM5982219
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GSM5982188 GSM5982189
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GSM5982158 GSM5982159
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GSM5982244 GSM5982245
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GSM5982206 GSM5982207
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GSM5982214 GSM5982215
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GSM5982154 GSM5982155
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GSM5982198 GSM5982199
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GSM5982182 GSM5982183
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GSM5982142 GSM5982143
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GSM5982194 GSM5982195
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GSM5982210 GSM5982211
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GSM5982146 GSM5982147
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GSM5982166 GSM5982167
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GSM5982230 GSM5982231
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GSM5982186 GSM5982187
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| Liver tissue |
GSM5982318 GSM5982319
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GSM5982300 GSM5982301
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GSM5982264 GSM5982265
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GSM5982272 GSM5982273
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GSM5982288 GSM5982289
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GSM5982354 GSM5982355
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GSM5982308 GSM5982309
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GSM5982350 GSM5982351
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GSM5982342 GSM5982343
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GSM5982348 GSM5982349
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GSM5982306 GSM5982307
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GSM5982248 GSM5982249
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GSM5982362 GSM5982363
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GSM5982338 GSM5982339
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GSM5982278 GSM5982279
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GSM5982296 GSM5982297
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GSM5982250 GSM5982251
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GSM5982336 GSM5982337
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GSM5982356 GSM5982357
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GSM5982280 GSM5982281
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GSM5982286 GSM5982287
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GSM5982292 GSM5982293
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GSM5982352 GSM5982353
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GSM5982340 GSM5982341
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GSM5982324 GSM5982325
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GSM5982260 GSM5982261
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GSM5982252 GSM5982253
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GSM5982358 GSM5982359
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GSM5982320 GSM5982321
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GSM5982312 GSM5982313
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GSM5982254 GSM5982255
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GSM5982294 GSM5982295
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GSM5982256 GSM5982257
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GSM5982328 GSM5982329
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GSM5982266 GSM5982267
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GSM5982344 GSM5982345
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GSM5982268 GSM5982269
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GSM5982290 GSM5982291
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GSM5982276 GSM5982277
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GSM5982332 GSM5982333
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GSM5982316 GSM5982317
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GSM5982284 GSM5982285
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GSM5982334 GSM5982335
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GSM5982304 GSM5982305
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GSM5982274 GSM5982275
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GSM5982360 GSM5982361
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GSM5982322 GSM5982323
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GSM5982330 GSM5982331
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GSM5982270 GSM5982271
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GSM5982314 GSM5982315
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GSM5982298 GSM5982299
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GSM5982258 GSM5982259
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GSM5982310 GSM5982311
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GSM5982326 GSM5982327
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GSM5982262 GSM5982263
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GSM5982282 GSM5982283
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GSM5982346 GSM5982347
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GSM5982302 GSM5982303
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Submission Date: Mar 29, 2022
Summary: We report transcriptomic profiling from bulk heart, kidney, and liver tissues for 58 strains of the inbred mouse Collaborative Cross (CC). Each strain is represented by a male/female pair. Reads were first aligned to the pooled transcriptomes of the eight founder strains of the CC and then total gene counts were quantified using the EMASE and GBRS software tools. Total read counts can be further normalized for use in differential gene expression analysis, expression quantitative trait locus (eQTL) analysis, and integrative analyses with other -omic data sets measured on the same samples, including proteomics and phosphoproteomics.
GEO Accession ID: GSE199702
PMID: No Pubmed ID
Submission Date: Mar 29, 2022
Summary: We report transcriptomic profiling from bulk heart, kidney, and liver tissues for 58 strains of the inbred mouse Collaborative Cross (CC). Each strain is represented by a male/female pair. Reads were first aligned to the pooled transcriptomes of the eight founder strains of the CC and then total gene counts were quantified using the EMASE and GBRS software tools. Total read counts can be further normalized for use in differential gene expression analysis, expression quantitative trait locus (eQTL) analysis, and integrative analyses with other -omic data sets measured on the same samples, including proteomics and phosphoproteomics.
GEO Accession ID: GSE199702
PMID: No Pubmed ID
Visualize Samples
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Precomputed Differential Gene Expression
Differential expression signatures are automatically computed using the limma R package.
More options for differential expression are available to compute below.
Signatures:
No precomputed signatures are currently available for this study. You can compute differential gene expression on the fly below:
Select conditions:
Control Condition
Perturbation Condition
Only conditions with at least 1 replicate are available to select
Differential expression signatures can be computed using DESeq2 or characteristic direction.
This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.
