Memory loss is a real issue that is extremely hard to predict other than from family heritage. Multiple genes can cause memory loss. (https://www.alz.org/alzheimers-dementia/what-is-alzheimers/causes-and-risk-factors/genetics#:~:text=APOE%2De4%20is%20one%20of,increased%20risk%20of%20developing%20Alzheimer%27s). The hippocampus is one of the core parts of the memory circuit of the brain. Fortunately, there have been studies to tell how key of a role it plays in the brain and what genes are key to its function.(https://www.medicalnewstoday.com/articles/313295#:~:text=The%20hippocampus%20helps%20humans%20process,memories%20involve%20pathways%20or%20routes.) A few of these genes are in the tables below, along with hippocampal reaction time and activation. These will be able to show how affected a key region of the memory loss problem is by a certain combinations of genes.

# memory loss

import pandas as pd

table1 = pd.read_csv('suppltable-1.csv', sep=",", header=0)
table2 = pd.read_csv('suppltable-2.csv', sep=",", header=0)
table3 = pd.read_csv('suppltable-3.csv', sep=",", header=0)
table4 = pd.read_csv('suppltable-4.csv', sep=",", header=0)
table5 = pd.read_csv('suppltable-5.csv', sep=",", header=0)
table6 = pd.read_csv('suppltable-6.csv', sep=",", header=0)

table1

	ID	Day	treatment	training	trial	trialNum	ShockOnOff	PairedPartner	TotalPath	Speed	...	pTimeShockZone	pTimeCCW	pTimeOPP	pTimeCW	RayleigLength	RayleigAngle	Min50.RngLoBin	AnnularSkewnes	AnnularKurtosis	ShockPerEntrance
0	15140A	1	conflict.trained	trained	Pre	1	Off	15140B	22.68	3.78	...	0.2277	0.2583	0.1788	0.3352	0.11	330.67	60	0.88	3.13	0.000000
1	15140A	1	conflict.trained	trained	T1	2	On	15140B	19.36	3.23	...	0.0211	0.6961	0.2049	0.0779	0.65	112.66	130	1.81	6.70	1.166667
2	15140A	1	conflict.trained	trained	T2	3	On	15140B	15.01	2.50	...	0.0092	0.6413	0.3245	0.0250	0.78	124.87	150	1.87	8.91	1.500000
3	15140A	1	conflict.trained	trained	T3	4	On	15140B	14.39	2.40	...	0.0069	0.5790	0.4018	0.0123	0.80	128.39	150	2.84	12.51	1.000000
4	15140A	2	conflict.trained	trained	Retest	5	On	15140B	14.04	2.34	...	0.0026	0.2945	0.6300	0.0729	0.72	159.36	170	2.42	11.83	1.000000
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
301	15148D	2	conflict.yoked	yoked	Retest	5	On	15148C	11.41	1.90	...	0.2085	0.1145	0.2694	0.4076	0.31	262.12	300	1.24	6.83	0.307692
302	15148D	2	conflict.yoked	yoked	T4_C1	6	On	15148C	17.76	2.96	...	0.1425	0.1573	0.2520	0.4483	0.20	264.67	320	1.23	5.03	1.941176
303	15148D	2	conflict.yoked	yoked	T5_C2	7	On	15148C	15.00	2.50	...	0.1518	0.2156	0.3478	0.2848	0.08	158.40	170	1.42	5.11	1.866667
304	15148D	2	conflict.yoked	yoked	T6_C3	8	On	15148C	12.49	2.08	...	0.2318	0.1614	0.2757	0.3311	0.14	297.44	340	1.40	5.49	1.437500
305	15148D	3	conflict.yoked	yoked	Retention	9	Off	15148C	4.92	0.82	...	0.1629	0.2525	0.3438	0.2408	0.14	125.49	200	-0.01	1.97	0.000000

306 rows × 34 columns

table2

	treatment	trial	trialNum	m	se	measure
0	standard.yoked	Pre	1	0.000	0.00	NumShock
1	standard.yoked	Retention	9	0.000	0.00	NumShock
2	standard.yoked	Retest	5	4.000	1.20	NumShock
3	standard.yoked	T1	2	7.000	0.85	NumShock
4	standard.yoked	T2	3	5.000	2.12	NumShock
...	...	...	...	...	...	...
139	conflict.trained	T2	3	0.007	0.00	pTimeShockZone
140	conflict.trained	T3	4	0.009	0.01	pTimeShockZone
141	conflict.trained	T4_C1	6	0.046	0.01	pTimeShockZone
142	conflict.trained	T5_C2	7	0.011	0.00	pTimeShockZone
143	conflict.trained	T6_C3	8	0.009	0.00	pTimeShockZone

144 rows × 6 columns

table3

	ID	treatment	trial	trialNum	PC1	PC2
0	15140A	conflict.trained	Pre	1	-2.963453	-2.392646
1	15140A	conflict.trained	T1	2	0.903697	-2.064785
2	15140A	conflict.trained	T2	3	2.480396	-0.148906
3	15140A	conflict.trained	T3	4	3.823651	-0.256449
4	15140A	conflict.trained	Retest	5	5.439012	-0.285502
...	...	...	...	...	...	...
301	15148D	conflict.yoked	Retest	5	-0.714399	1.128465
302	15148D	conflict.yoked	T4_C1	6	-2.026176	-1.792379
303	15148D	conflict.yoked	T5_C2	7	-1.687280	-0.437753
304	15148D	conflict.yoked	T6_C3	8	-1.037671	0.329022
305	15148D	conflict.yoked	Retention	9	-2.302549	3.589102

306 rows × 6 columns

table4

	tissue	gene	lfc	padj	logpadj	comparison	direction
0	DG	1190002N15Rik	1.64	2.450000e-04	3.61	yoked vs. trained	trained
1	DG	A830010M20Rik	1.53	7.890000e-07	6.10	yoked vs. trained	trained
2	DG	Abhd2	0.86	1.530000e-02	1.81	yoked vs. trained	trained
3	DG	Acan	1.97	4.540000e-09	8.34	yoked vs. trained	trained
4	DG	Adamts1	1.88	1.880000e-03	2.73	yoked vs. trained	trained
...	...	...	...	...	...	...	...
209	DG	Zfp207	-0.40	9.730000e-02	1.01	yoked vs. trained	yoked
210	DG	Zfp275	1.23	1.200000e-02	1.92	yoked vs. trained	trained
211	DG	Zfp654	0.77	9.790000e-02	1.01	yoked vs. trained	trained
212	DG	Zfp668	-0.62	6.990000e-02	1.16	yoked vs. trained	yoked
213	DG	Zfp869	1.15	9.730000e-02	1.01	yoked vs. trained	trained

214 rows × 7 columns

table5

	tissue	gene	lfc	padj	logpadj	comparison	direction
0	CA1	1110032F04Rik	3.70	0.07540	1.12	standard.yoked vs. conflict.yoked	conflict.yoked
1	CA1	1600002K03Rik	-4.51	0.05710	1.24	standard.yoked vs. conflict.yoked	standard.yoked
2	CA1	1810030O07Rik	-1.73	0.06860	1.16	standard.yoked vs. conflict.yoked	standard.yoked
3	CA1	2010107G23Rik	-2.14	0.01760	1.75	standard.yoked vs. conflict.yoked	standard.yoked
4	CA1	2210013O21Rik	-2.38	0.05170	1.29	standard.yoked vs. conflict.yoked	standard.yoked
...	...	...	...	...	...	...	...
914	CA1	Znfx1	-1.18	0.09140	1.04	standard.yoked vs. conflict.yoked	standard.yoked
915	CA1	Zscan26	-0.91	0.03020	1.52	standard.yoked vs. conflict.yoked	standard.yoked
916	CA1	Ubash3a	-5.79	0.03260	1.49	standard.yoked vs. conflict.yoked	standard.yoked
917	CA3	Sco2	7.48	0.00417	2.38	standard.yoked vs. conflict.yoked	conflict.yoked
918	CA3	Tbc1d16	-2.00	0.07050	1.15	standard.yoked vs. conflict.yoked	standard.yoked

919 rows × 7 columns

table6

	rowname	PC1	Naf1	Ptgs2	Rgs2	Hist1h1d	Col10a1	Arc	Hspb3	Npas4	...	Areg	Hist1h3i	Armcx5	Atf3	Syt4	Nexn	Hoxc4	Abra	Fosl2	Ubc
0	PC1	1.000000	0.861710	0.840046	0.833975	0.815008	0.812722	0.805927	0.803447	0.802382	...	0.784206	0.779006	0.775536	0.774300	0.774266	0.771603	0.765295	0.764433	0.762014	0.753432
1	Naf1	0.861710	1.000000	0.853795	0.810304	0.822065	0.802797	0.747035	0.682500	0.813929	...	0.584414	0.617801	0.702905	0.732662	0.820325	0.774886	0.884765	0.741153	0.802733	0.796188
2	Ptgs2	0.840046	0.853795	1.000000	0.942791	0.747602	0.885850	0.933437	0.716260	0.963923	...	0.648379	0.622406	0.732795	0.879031	0.883762	0.743377	0.748623	0.844199	0.920882	0.873972
3	Rgs2	0.833975	0.810304	0.942791	1.000000	0.708767	0.945479	0.898791	0.694389	0.877231	...	0.531741	0.578752	0.832968	0.854276	0.848425	0.782270	0.769571	0.900119	0.942091	0.930976
4	Hist1h1d	0.815008	0.822065	0.747602	0.708767	1.000000	0.747891	0.609192	0.602161	0.712381	...	0.619715	0.477320	0.635545	0.629609	0.719632	0.746408	0.816151	0.623478	0.717901	0.595381
5	Col10a1	0.812722	0.802797	0.885850	0.945479	0.747891	1.000000	0.842001	0.658760	0.860330	...	0.509401	0.459277	0.800312	0.794113	0.831175	0.799600	0.798270	0.844814	0.881100	0.906915
6	Arc	0.805927	0.747035	0.933437	0.898791	0.609192	0.842001	1.000000	0.662738	0.903617	...	0.664667	0.537830	0.738534	0.963703	0.880583	0.589693	0.601560	0.810139	0.885906	0.911216
7	Hspb3	0.803447	0.682500	0.716260	0.694389	0.602161	0.658760	0.662738	1.000000	0.708906	...	0.739534	0.730282	0.700024	0.592542	0.538325	0.732298	0.508571	0.480273	0.604450	0.577074
8	Npas4	0.802382	0.813929	0.963923	0.877231	0.712381	0.860330	0.903617	0.708906	1.000000	...	0.678595	0.587246	0.674063	0.842902	0.817552	0.724191	0.670742	0.767242	0.865242	0.816451
9	Fzd5	0.798759	0.822728	0.902913	0.880734	0.686966	0.882801	0.858059	0.704945	0.911606	...	0.706219	0.623661	0.718331	0.782778	0.750272	0.780524	0.735385	0.805505	0.907861	0.857066
10	Acan	0.784206	0.806749	0.871607	0.828620	0.744796	0.812073	0.871398	0.710476	0.859979	...	0.680139	0.513611	0.788082	0.848874	0.823281	0.761335	0.697077	0.719405	0.884047	0.834426
11	Areg	0.784206	0.584414	0.648379	0.531741	0.619715	0.509401	0.664667	0.739534	0.678595	...	1.000000	0.719754	0.503143	0.593103	0.484727	0.469028	0.385089	0.459426	0.562174	0.457249
12	Hist1h3i	0.779006	0.617801	0.622406	0.578752	0.477320	0.459277	0.537830	0.730282	0.587246	...	0.719754	1.000000	0.526630	0.436253	0.420689	0.589943	0.520603	0.553285	0.530151	0.442282
13	Armcx5	0.775536	0.702905	0.732795	0.832968	0.635545	0.800312	0.738534	0.700024	0.674063	...	0.503143	0.526630	1.000000	0.665476	0.774165	0.738661	0.655356	0.734390	0.792222	0.786702
14	Atf3	0.774300	0.732662	0.879031	0.854276	0.629609	0.794113	0.963703	0.592542	0.842902	...	0.593103	0.436253	0.665476	1.000000	0.840290	0.538641	0.574977	0.762065	0.836550	0.900746
15	Syt4	0.774266	0.820325	0.883762	0.848425	0.719632	0.831175	0.880583	0.538325	0.817552	...	0.484727	0.420689	0.774165	0.840290	1.000000	0.668123	0.796928	0.821299	0.847184	0.839796
16	Nexn	0.771603	0.774886	0.743377	0.782270	0.746408	0.799600	0.589693	0.732298	0.724191	...	0.469028	0.589943	0.738661	0.538641	0.668123	1.000000	0.849573	0.734314	0.708273	0.650460
17	Hoxc4	0.765295	0.884765	0.748623	0.769571	0.816151	0.798270	0.601560	0.508571	0.670742	...	0.385089	0.520603	0.655356	0.574977	0.796928	0.849573	1.000000	0.798651	0.753632	0.702854
18	Abra	0.764433	0.741153	0.844199	0.900119	0.623478	0.844814	0.810139	0.480273	0.767242	...	0.459426	0.553285	0.734390	0.762065	0.821299	0.734314	0.798651	1.000000	0.830302	0.867754
19	Fosl2	0.762014	0.802733	0.920882	0.942091	0.717901	0.881100	0.885906	0.604450	0.865242	...	0.562174	0.530151	0.792222	0.836550	0.847184	0.708273	0.753632	0.830302	1.000000	0.888569
20	Ubc	0.753432	0.796188	0.873972	0.930976	0.595381	0.906915	0.911216	0.577074	0.816451	...	0.457249	0.442282	0.786702	0.900746	0.839796	0.650460	0.702854	0.867754	0.888569	1.000000

21 rows × 22 columns

We will look into the gene expression and see if it predicts if a gene expressed or not expressed is an indicator of early memory loss. Different gene expression is in different tables and the status of the hippocampus is also indicated. The correlation between the two will be measured.